880 resultados para Automatic tagging of music


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This paper presents a study made in a field poorly explored in the Portuguese language – modality and its automatic tagging. Our main goal was to find a set of attributes for the creation of automatic tag- gers with improved performance over the bag-of-words (bow) approach. The performance was measured using precision, recall and F1. Because it is a relatively unexplored field, the study covers the creation of the corpus (composed by eleven verbs), the use of a parser to extract syntac- tic and semantic information from the sentences and a machine learning approach to identify modality values. Based on three different sets of attributes – from trigger itself and the trigger’s path (from the parse tree) and context – the system creates a tagger for each verb achiev- ing (in almost every verb) an improvement in F1 when compared to the traditional bow approach.

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Smart contracts are the most advanced blockchain applications. They can also be used in the contractual domain for the encoding and automatic execution of contract terms. Smart contracts already existed before the blockchain, but they take advantage of the characteristics of that technology. Namely, the decentralised and immutable characters of the blockchain determine that no single contracting party can control, modify, or interrupt the execution of smart contracts. As every new phenomenon, blockchain-based smart contracts have attracted the attention of institutions. For example, in its Resolution of 3 October 2018 on distributed ledger technologies and blockchain, the European Parliament has stressed the need to undertake an in-depth assessment of the legal implications,starting from the analysis of existing legal frameworks. Indeed, the present research thesis aims to verify how blockchain-based smart contracts fit into contract law. To this end, the analysis starts from the most discussed and relevant aspects and develops further considerations. Before that, it provides a detailed description and clarifications about the characteristics, the functioning, and the development of the technology, which is an essential starting point for a high-level quality legal analysis. It takes into considerations already existing rules concerning the use of technology in the life cycle of contracts, from vending machines to computable contracts, and verifies its applicability to blockchain-based smart contracts. The work does not limit to consider the mere technology, but some concrete scenarios of adoption of blockchain-based smart contracts in the contractual domain. Starting from the latter, it focuses on the implications of blockchain-based smart contracts on contract formation, contract performance, and applicable law and jurisdiction.

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In the early twentieth century, musicology was established as an academic discipline in the United States. Nonetheless, with the exception of Iberian medieval and Renaissance repertories, U.S. scholars largely overlooked the music of the Spanish- and Portuguese- speaking world. Why should this have been the case, especially in light of Spain’s strong historical presence in the United States? This autobiographical essay examines this question by tracing the career of an individual musicologist, the Hispanist musicologist Carol A. Hess. Evaluated here are disciplinary shifts in U.S. musicology —methodological, philosophical, and ideological— over the past thirty years. These transformations have combined to make this repertory a viable field of study today. Musicologists in the United States can now make their careers by specializing in Iberian and Latin American music, as well as the music of the Hispanic diaspora. They research topics ranging from the avant-garde composer Llorenç Barber to the rapper Nach Scratch or the popular bandleader Xavier Cugat and his U.S. audiences of the 1940s, while others also pursue the time-tested areas of medieval and Renaissance music. Iberian and Latin American music is regularly offered in postsecondary institutions while instructors now have a variety of textbooks and other pedagogical resources from which to choose. All add up to a disciplinary freedom that would have been unthinkable only a few decades ago.

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Recently, massive open online courses (MOOCs) have been offering a new online approach in the field of distance learning and online education. A typical MOOC course consists of video lectures, reading material and easily accessible tests for students. For a computer programming course, it is important to provide interactive, dynamic, online coding exercises and more complex programming assignments for learners. It is expedient for the students to receive prompt feedback on their coding submissions. Although MOOC automated programme evaluation subsystem is capable of assessing source programme files that are in learning management systems, in MOOC systems there is a grader that is responsible for evaluating students’ assignments with the result that course staff would be required to assess thousands of programmes submitted by the participants of the course without the benefit of an automatic grader. This paper presents a new concept for grading programming submissions of students and improved techniques based on the Java unit testing framework that enables automatic grading of code chunks. Some examples are also given such as the creation of unique exercises by dynamically generating the parameters of the assignment in a MOOC programming course combined with the kind of coding style recognition to teach coding standards.

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Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

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In the agri-food sector, measurement and monitoring activities contribute to high quality end products. In particular, considering food of plant origin, several product quality attributes can be monitored. Among the non-destructive measurement techniques, a large variety of optical techniques are available, including hyperspectral imaging (HSI) in the visible/near-infrared (Vis/NIR) range, which, due to the capacity to integrate image analysis and spectroscopy, proved particularly useful in agronomy and food science. Many published studies regarding HSI systems were carried out under controlled laboratory conditions. In contrast, few studies describe the application of HSI technology directly in the field, in particular for high-resolution proximal measurements carried out on the ground. Based on this background, the activities of the present PhD project were aimed at exploring and deepening knowledge in the application of optical techniques for the estimation of quality attributes of agri-food plant products. First, research activities on laboratory trials carried out on apricots and kiwis for the estimation of soluble solids content (SSC) and flesh firmness (FF) through HSI were reported; subsequently, FF was estimated on kiwis using a NIR-sensitive device; finally, the procyanidin content of red wine was estimated through a device based on the pulsed spectral sensitive photometry technique. In the second part, trials were carried out directly in the field to assess the degree of ripeness of red wine grapes by estimating SSC through HSI, and finally a method for the automatic selection of regions of interest in hyperspectral images of the vineyard was developed. The activities described above have revealed the potential of the optical techniques for sorting-line application; moreover, the application of the HSI technique directly in the field has proved particularly interesting, suggesting further investigations to solve a variety of problems arising from the many environmental variables that may affect the results of the analyses.

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This research proposes a solution for integrating RFID - Radio Frequency Identification technology within a structure based on CFRPs - Carbon Fiber Reinforced Polymers. Therefore, the main objective is to use technology to monitor and track composite components during manufacturing and service life. The study can be divided into two macro-areas. The first portion of the research evaluates the impact of the composite materials used on transmitting the electromagnetic signal to and from the tag. RFID technology communicates through radio frequencies to to track and trace items associated with the tags. In the first instance, a feasibility study was carried out to assess using commercially available tags. Then, after evaluating different solutions, it was decided to incorporate the tags into coupons during production. The second portion of the research is focused on evaluating the impact on the composite material's resistance to tag embedding. It starts with designing tensile test specimens through the FEM model with different housing configurations. Subsequently, the best configuration was tested in the facilities of the In the Faculty of Aerospace Engineering at TU Delft, particularly in the Structure & Materials Laboratory, two tests were conducted: the first one based on ASTM D3039/D3039 - 14 - Standard Test Method for Tensile Properties of Polymer Matrix Composite Materials, the second one dividing the path to failure into failure intervals in a load-unload-reload. Both tests were accompanied by instruments such as DIC, AE, C-Scan and Optical Microscopes. The expected result of the inclusion of RFID tags in composite components is that it brings added value to the parts with which it is associated without affecting too much its mechanical properties. This comes first from the automatic identification of RFID during the production cycle and its useful life. As a result, improvements were made in the design of production facilities.

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Base cutting and feeding into harvesters of plants lying close to the ground surface require an efficient sweeping action of the cutting mechanism. It is not the case of conventional sugarcane harvesters which have rigid blades mounted on discs capable to contaminate the cane with dirt as well as damage the ratoons. The objective of this work was to simulate the sweeping performance of a segmented base cutter. The model was developed using the laws of dynamic. Simulation included two rotational speeds (400 and 600 rpm), two cutting heights (0.12 and 0.13 m) and two disk tilting angles (-10º and -12º). The simulated sweeping angle varied between 56º and 193º, which are very promising as a mean to cutting and feeding cane sticks lying on the ground. Cutting height was the variable that affected sweeping action the most. This behavior indicates the need to have an automatic control of the cutting disk height in order to keep good sweeping performance as the harvester moves forward.

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This paper describes the development of a relational database and a tool for viewing MODIS NDVI temporal profile, using data from MOD09Q1 product, specifically the surface bidirectional reflectance factor relative to the RED and NIR wavelength, mosaic of 8-day temporal composition, and the quality band, in sugarcane fields in the state of São Paulo, for analysis of the late stubble-cane maturation. From sugarcane farms were obtained the historical data about yield, soil, variety, location of the each pixel for each subregion monitored. All data were integrated in a database developed in PostgreSQL. The tool was implemented using Java language and allowed a fast and automatic way of analyzing sugarcane phenological patterns. It concluded that the MODIS NDVI temporal profile using data from MOD09Q1 product is able to subsidize the monitoring of phenological changes in the sugarcane.

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Universidade Estadual de Campinas . Faculdade de Educação Física