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Optical character recognition (OCR) – the fully automated transcription of text appearing in a digitized image – offers transformative opportunities for the scholarly study of written materials produced prior to the digital age. Digitization, in the sense of photographic reproduction, is a largely straightforward, mechanical process, and one n game with significant value in its own right for purposes of preservation as well as access to rare materials. As a result, hundreds of millions of pages of pre-modern Chinese works have been digitized by libraries and academic institutions around the world – a significant portion of this increasingly being made static electricity how it works freely available online.

To make use of this material efficiently, transcriptions of the textual content of these images are needed. Given the enormous volume of image data in existence – and its continual production as digitization continues – this task is only feasible if it can be fully automated: performed by software without manual intervention. Individually, reliable transcriptions produced by OCR offer enormous time savings to researchers, making it possible to efficiently navigate materials in ways not possible without digital transcription. In aggregate, however, these transcriptions make possible electricity billy elliot chords entirely new ways of exploring historical materials – making it possible to rapidly identify material that one suspects may exist somewhere, without knowing in advance where that might actually be. It is also a prerequisite also to virtually any type of statistical analysis of these materials – the potential utility of which continues to increase as a larger and larger proportion of the extant corpus hp gas online complaint is transcribed.

This paper introduces a procedure for OCR of pre-modern Chinese written materials, both printed and handwritten, describing the complete process from digitized image through to automated transcription and manual correction of remaining errors gas zauberberg 1, with particular attention to issues arising in this domain. The process described has been applied to over 25 million pages of pre-modern Chinese works, and the paper also introduces the Chinese Text Project platform used to both make these results available to scholars as well as provide a distributed gas vs diesel, crowdsourced mechanism for facilitating manual corrections at scale as well as further analysis of these materials.

The phenomenon of text reuse – syntactically and semantically similar fragments of text repeated apparently independently in multiple pieces of writing, and gas bubble in back often in works purporting to be composed by entirely different authors – is extremely widespread in early Chinese literature. Such reuse is typically unattributed, and its existence is often revealed only through painstaking comparison with other pieces of potentially related writing. Computational methods have for the first time made feasible the comprehensive identification of such reuse throughout large corpora of material, and have thus made practical studies based on patterns of reuse which emerge at much larger scales than had previously been possible npower gas price reduction to consider.

This work uses network analysis to investigate patterns of text reuse in the early Chinese corpus and the relationship between these patterns and difficult questions of authorship attribution within these texts. Using detailed data on individual instances of text reuse created through an exhaustive automated study of the entire transmitted corpus of Chinese from the earliest transmitted works through to those dating prior to the end of the Han dynasty (220 AD), this electricity notes class 10 pdf study demonstrates the utility of network visualization and analysis in identifying and exploring patterns of text reuse which shed light on the authorship of these early materials.

Despite gas guzzler tax a growing interest in digital humanities as a field of study and focus of specialization, significant barriers to the adoption of digital techniques remain within research and teaching in practice in many humanities disciplines. While an increasing number of humanities scholars have demonstrated willingness to invest time and effort in cultivating necessary technical skills, in practice many more are prevented from experimenting with digital methods due to perceived high barriers to entry. One approach to accelerate the adoption of digital techniques is to attempt to reduce the prerequisite technical skills required arkansas gas and oil commission to apply techniques to research data in practice through the creation of platforms and tools able to bridge technical gaps for some of the most powerful and generally applicable use cases.

With this goal in mind, this talk introduces a suite of browser-based text analysis tools electricity use designed for pre-modern Chinese materials and intended to easily integrate into scholarly workflows, including in particular those common in Chinese literature, philosophy, and history departments. Major goals include accessibility of the tools themselves, as well as transparency of their working and ability to introspect the mechanisms underwriting the quadcopter gas engine results and visualizations produced. By enabling rapid exploration of arbitrarily chosen textual materials while also providing insight into the algorithms used, these tools have pedagogical applications in addition to research uses, and are already in use teaching at several institutions.