Dairying in the Waikato Region of New Zealand: An overview of historical statistics

The dairy industry is an important contributor to the economy of the Waikato region of New Zealand. An understanding of the history and development of the dairy sector in the different districts of the Waikato region is important in terms of informing future policy. Unfortunately there are currently no consistent long-run spatially disaggregated data sets available for the districts of the Waikato region that extend any further back than 1990. In this paper, we present the current state of dairy farming data available for the territorial local authorities within the Waikato region, and briefly discuss a set of methods that will be employed to develop consistent long-run spatially disaggregated data series for (i) milk production; (ii) total number of productive dairy cattle; (iii) total number of dairy farms; and (iv) total effective hectares devoted to dairy production

Entanglement witnesses and a loophole problem

We consider a possible detector-efficiency loophole in experiments that detect entanglement via the local measurement of witness operators. Here, only local properties of the detectors are known. We derive a general threshold for the detector efficiencies which guarantees that a negative expectation value of a witness is due to entanglement, rather than to erroneous detectors. This threshold depends on the local decomposition of the witness and its measured expectation value. For two-qubit witnesses we find the local operator decomposition that is optimal with respect to closing the loophole.Comment: 5 pages, 2 figures, published versio

Cyber Threat Report 02 February 2019

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Cyber Threat Report 03 January 2019

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Cyber Threat Report 04 March 2019

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Cyber Threat Report May 06, 2019

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Cyber Threat Report 04 April 2019

Army Cyber Institute Cyber Threat Report Tech Trends: Stories and Highlights MySpace loses 50 million songs in failed server migration Microsoft Takes Down 99 Hacker-Controlled Websites Hackers Hijacked ASUS Software Updates to Install Backdoors North Korean Hackers Behind $571M Crypto Heist

The Computational Attitude in Music Theory

Music studies’s turn to computation during the twentieth century has engendered particular habits of thought about music, habits that remain in operation long after the music scholar has stepped away from the computer. The computational attitude is a way of thinking about music that is learned at the computer but can be applied away from it. It may be manifest in actual computer use, or in invocations of computationalism, a theory of mind whose influence on twentieth-century music theory is palpable. It may also be manifest in more informal discussions about music, which make liberal use of computational metaphors. In Chapter 1, I describe this attitude, the stakes for considering the computer as one of its instruments, and the kinds of historical sources and methodologies we might draw on to chart its ascendance. The remainder of this dissertation considers distinct and varied cases from the mid-twentieth century in which computers or computationalist musical ideas were used to pursue new musical objects, to quantify and classify musical scores as data, and to instantiate a generally music-structuralist mode of analysis. I present an account of the decades-long effort to prepare an exhaustive and accurate catalog of the all-interval twelve-tone series (Chapter 2). This problem was first posed in the 1920s but was not solved until 1959, when the composer Hanns Jelinek collaborated with the computer engineer Heinz Zemanek to jointly develop and run a computer program. Recognizing the transformation wrought on modern statistics and communications technology by information theory, I revisit Abraham Moles’s book Information Theory and Esthetic Perception (orig. 1958) and use its vocabulary to contextualize contemporary information-theoretic work on music that various evokes the computational mind by John. R. Pierce and Mary Shannon, Wilhelm Fucks, and Henry Quastler (Chapter 3). I conclude with a detailed look into a score-segmentation algorithm of the influential American music theorist Allen Forte (Chapter 4). Forte was a skilled programmer who spent several years at MIT in the 1960s, with cutting-edge computers and the company of first-rank figures in the nascent fields of computer science and artificial intelligence. Each one of the researchers whose work is treated in these case studies—at some stage in their relationship with music—adopted what I call the computational attitude to music, to varying degrees and for diverse ends. Of the many questions this dissertation seeks to answer: what was gained by adopting such an attitude? What was lost? Having understood these past explorations of the computational attitude to music, we are better suited ask of ourselves the same questions today