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"Data structures (Computer science)"
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The stuff of bits : an essay on the materialities of information
\"The central topic of 'The Stuff of Bits' is the materialities of information. This term often brings to mind the materiality of information infrastructures - server farms, air conditioning, fiber optic cable routes, and distributed storage. By contrast, 'The Stuff of Bits' focuses on digital information itself as something with which we - as designers, as users, as citizens, as customers, and as human beings - have a material engagement. The book is anchored by four case studies - one on computer emulation, one on spreadsheets, one on databases, and one on network architectures - organized in terms of the scopes of engagement. Through these cases, a common analytic strategy is to identify not just their materiality but their materialities, that is, not just the brute fact of their material forms but the specific material properties that they display and the consequences of those properties - properties like granularity, transparency, directness, weight, and malleability. The idea is that, in the realm of the digital, everything may be reduced to 'bits' but those bits are not all of equal significance; particular encodings reflect particular needs and expectations of change, adaptation, and evolution. To a certain extent this is similar to 'constraints' and 'affordances' in Don Norman's Six Principles of Design and the driving force behind the Platform Studies series, in that different mediums, or materialities, promote distinct use and reception. As Paul Dourish writes in the Introduction to this book, 'material arrangements of information - how it is represented and how that shapes how it can be put to work - matters significantly for our experience of information and information systems'\"-- Provided by publisher.
Book
Blockchain basics : a non-technical introduction in 25 steps
In 25 concise steps, you will learn the basics of blockchain technology.No mathematical formulas, program code, or computer science jargon are used.No previous knowledge in computer science, mathematics, programming, or cryptography is required.Terminology is explained through pictures, analogies, and metaphors.
eBook
Countering the cloud : thinking with and against data infrastructures
How do cables and data centers think? This book investigates how information infrastructures enact particular forms of knowledge. It juxtaposes the pervasive logics of speed, efficiency, and resilience with more communal and ecological ways of thinking and being, turning technical solutions back into open questions about what society wants and what infrastructures should do. Moving from data centers in Hong Kong to undersea cables in Singapore and server clusters in China, Munn combines rich empirical material with insights drawn from media and cultural studies, sociology, and philosophy. This critical analysis stresses that infrastructures are not just technical but deeply epistemological, privileging some actions and actors while sidelining others. This innovative exploration of the values and visions at the heart of our technologies will interest students, scholars, and researchers in the areas of communication studies, digital media, technology studies, sociology, philosophy of technology, information studies, and geography.
Book
SciPy 1.0: fundamental algorithms for scientific computing in Python
SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
This Perspective describes the development and capabilities of SciPy 1.0, an open source scientific computing library for the Python programming language.
Journal Article
A common-sense guide to data structures and algorithms : level up your core programming skills
\"A practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language ... Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software .. You'encounter a single keyword that can give your code a turbo boost\"-- Provided by publisher.
Book
Object detection using YOLO: challenges, architectural successors, datasets and applications
Object detection is one of the predominant and challenging problems in computer vision. Over the decade, with the expeditious evolution of deep learning, researchers have extensively experimented and contributed in the performance enhancement of object detection and related tasks such as object classification, localization, and segmentation using underlying deep models. Broadly, object detectors are classified into two categories viz. two stage and single stage object detectors. Two stage detectors mainly focus on selective region proposals strategy via complex architecture; however, single stage detectors focus on all the spatial region proposals for the possible detection of objects via relatively simpler architecture in one shot. Performance of any object detector is evaluated through detection accuracy and inference time. Generally, the detection accuracy of two stage detectors outperforms single stage object detectors. However, the inference time of single stage detectors is better compared to its counterparts. Moreover, with the advent of YOLO (You Only Look Once) and its architectural successors, the detection accuracy is improving significantly and sometime it is better than two stage detectors. YOLOs are adopted in various applications majorly due to their faster inferences rather than considering detection accuracy. As an example, detection accuracies are 63.4 and 70 for YOLO and Fast-RCNN respectively, however, inference time is around 300 times faster in case of YOLO. In this paper, we present a comprehensive review of single stage object detectors specially YOLOs, regression formulation, their architecture advancements, and performance statistics. Moreover, we summarize the comparative illustration between two stage and single stage object detectors, among different versions of YOLOs, applications based on two stage detectors, and different versions of YOLOs along with the future research directions.
Journal Article
A review on genetic algorithm: past, present, and future
In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching.
Journal Article
Handbook of Data Quality
This multi-pronged approach to data quality management covers Organization: processes, policies and standards needed to set data quality objectives; Architecture: the technological landscape for deploying them and Computation: required tools and techniques.
eBook