685 research outputs found

    Developing a Scheduling Module For Construction Management Labs

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    The Cal Poly Construction Management Department is renowned as one of the best programs in the nation. From holding one of the highest competition success rates to almost 100% job placement right out of school for graduates, Cal Poly undoubtedly lives up to that reputation. With that, in order to ensure that the department continues to produce well rounded graduates, it is crucial to regularly assess any potential shortcomings that the construction management curriculum may possess. As one of the three sides of the construction management triangle, the ability to read and create a construction schedule is a crucial skill for any project engineer or manager to possess. There is a broad spectrum of elements that go into creating a project schedule: from the programs, to the sequencing, to the overall logistics. This topic is something that is lacking in the current curriculum. This construction scheduling module would add to the overall Cal Poly Construction Management degree as well as benefit the graduates for the entirety of their careers

    Hvilke erfaringer har helsepersonell og pårørende med bruk av velferdsteknologi i demensomsorgen? Velferdsteknologiens muligheter og sårbarheter.

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    Velferdsteknologiens muligheter og sårbarheter byr på mange spennende utfordringer innenfor demens og teknologi. Omsorgssektoren har i flere år kjent til trygghetsalarm, komfyrvakt, døralarmer ol. Medio 2010 ble teknologi til eldre utvidet ved at det ble introdusert GPS til personer med kognitiv svikt. For ved å feste en GPS på en person med demens så ville ansatte på institusjoner og pårørende til en hver tid vite hvor personene befant seg. Formålet med denne Masteroppgaven ble å undersøke om forventningene til at teknologi ville ordne alt, samsvarte med pårørendes og ansattes erfaringer. Til denne oppgave ble det anvendt fem gjennomgående nøkkelbegreper: Velferdsteknologi, Pårørende, Forventninger, Erfaringer og Demens. Omsorgstjenesten i Oppegård kommune i Akershus hadde gjennom sine prosjekter samlet en del erfaringene om velferdsteknologi og kognitiv svikt. De ønsket at deres erfaringer kunne belyses grundigere sammen med annen forskning, gjerne i en masterstudie. Det ble valgt en kvalitativ metode der informanter fortalte om sine erfaringer knyttet til teknologi og hverdagsomsorg til personer med demens. Det ble også benyttet feltarbeid på flere arenaer som omhandlet velferdsteknologi og demens for og blant annet å ta del i pårørendes erfaringer. Det empiriske materiale antydet ganske tidlig at erfaringene med velferdsteknologi ikke var forenelige med forventningene til for eksempel bare sett på en GPS, så ser vi hvor han er. Skulle velferdsteknologi fungere bør mange personer involveres da personen med demens er ekstra sårbare og avhengig av et omsorgskollektiv med gode hjelpere som holder hverdagen i gang

    Comparing Probabilistic Models for Melodic Sequences

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    Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music features, such as underlying chords and typical melody transitions and dynamics. We assess the models for future prediction and compare their performance to a VMM, which is the current state of the art in melody generation. We show that both models perform significantly better than the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of the music genre significantly better than the VMM.Comment: in Proceedings of the ECML-PKDD 2011. Lecture Notes in Computer Science, vol. 6913, pp. 289-304. Springer (2011

    A response to Tom Barney

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68308/2/10.1177_096394709500400104.pd

    A Demonstration of Hierarchical Structure Usage in Expressive Timing Analysis by Model Selection Tests

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    © 2018 Technical Committee on Control Theory, Chinese Association of Automation. Analysing expressive timing in performed music can help machine to perform various perceptual tasks such as identifying performers and understand music structures in classical music. A hierarchical structure is commonly used for expressive timing analysis. This paper provides a statistical demonstration to support the use of hierarchical structure in expressive timing analysis by presenting two groups of model selection tests. The first model selection test uses expressive timing to determine the location of music structure boundaries. The second model selection test is matching a piece of performance with the same performer playing another given piece. Comparing the results of model selection tests, the preferred hierarchical structures in these two model selection tests are not the same. While determining music structure boundaries demands a hierarchical structure with more levels in the expressive timing analysis, a hierarchical structure with less levels helps identifying the dedicated performer in most cases

    Generation of folk song melodies using Bayes transforms

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    The paper introduces the `Bayes transform', a mathematical procedure for putting data into a hierarchical representation. Applicable to any type of data, the procedure yields interesting results when applied to sequences. In this case, the representation obtained implicitly models the repetition hierarchy of the source. There are then natural applications to music. Derivation of Bayes transforms can be the means of determining the repetition hierarchy of note sequences (melodies) in an empirical and domain-general way. The paper investigates application of this approach to Folk Song, examining the results that can be obtained by treating such transforms as generative models

    Information dynamics: patterns of expectation and surprise in the perception of music

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    This is a postprint of an article submitted for consideration in Connection Science © 2009 [copyright Taylor & Francis]; Connection Science is available online at:http://www.tandfonline.com/openurl?genre=article&issn=0954-0091&volume=21&issue=2-3&spage=8
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