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CORA.Repositori de Dades de Recerca
doi:10.34810/data457
Dataset. 2023

CARNATIC VARNAM DATASET

  • CompMusic
Audio music content----- They feature 7 varnams in 7 raagas sung by 5 young professional singers who received training for more than 15 years. They are all set to Adi taala. Measuring the intonation variations require absolutely clean pitch contours. For this, all the varṇaṁs are recorded without accompanying instruments, except the drone. Taala annotations----- The recordings are annotated with taala cycles, each annotation marking the starting of a cycle. We have later automatically divided each cycle into 8 equal parts. The annotations are made available as sonic visualizer annotation layers. Each annotation is of the format m.n where m is the cycle number and n is the division within the cycle. All m.1 annotations are manually done, whereas m.[2-8] are automatically labelled. Notations----- The notations for 7 varnams are procured from an archive curated by Shivkumar, in word document format. They are manually converted to a machine readable format (yaml). Each file is essentially a dictionary with section names of the composition as keys. Each section is represented as a list of cycles. Each cycle in turn has a list of divisions. Possible uses of the dataset----- The distinct advantage of this dataset is the free availability of the audio content. Along with the annotations, it can be used for melodic analyses: characterizing intonation, motif discovery and tonic identification. The availability of a machine readable notation files allows the dataset to be used for audio-score alignment.

Proyecto: //
DOI: https://doi.org/10.34810/data457
CORA.Repositori de Dades de Recerca
doi:10.34810/data457
HANDLE: https://doi.org/10.34810/data457
CORA.Repositori de Dades de Recerca
doi:10.34810/data457
PMID: https://doi.org/10.34810/data457
CORA.Repositori de Dades de Recerca
doi:10.34810/data457
Ver en: https://doi.org/10.34810/data457
CORA.Repositori de Dades de Recerca
doi:10.34810/data457

CORA.Repositori de Dades de Recerca
doi:10.34810/data458
Dataset. 2023

INDIAN ART MUSIC TONIC DATASETS

  • CompMusic
These datasets comprise audio excerpts and manually done annotations of the tonic pitch of the lead artist for each audio excerpt. Each excerpt is accompanied by its associated editorial metadata. These datasets can be used to develop and evaluate computational approaches for automatic tonic identification in Indian art music. These datasets have been used in several articles mentioned below. A majority of these datasets come from the CompMusic corpora of Indian art music, for which each recording is associated with a MBID. With the MBID other information can be obtained using the Dunya API. We here provide an overview of the tonic identification datasets. Datasets ------- The statistics about the datasets for tonic identification is listed in the table below. These six datasets are used in Gulati, S., Bellur, A., Salamon, J., Ranjani, H. G., Ishwar, V., Murthy, H. A., & Serra, X. (2014). Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation. Journal of New Music Research, 43(01), 55–73 for a comparative evaluation. To the best of our knowledge these are the largest datasets available for tonic identification for Indian art music. These datases vary in terms of the audio quality, recording period (decade), the number of recordings for Carnatic, Hindustani, male and female singers and instrumental and vocal excerpts. For a detailed information about these datasets we refer to Chapter 3 of this thesis (http://hdl.handle.net/10803/398984). The audio files corresponding to these datsets are made available on request for only research purposes. To obtain the files fill the FORM (https://goo.gl/forms/kWzpCsZW8DM7noW63). CompMusic Tonic Identification Datasets --- Datasets: CM1, CM2, CM3 Features: pitch + multipitch histogram + pitch histograms IITM Tonic Identification Datasets Datasets: IITM1, IITM2 Features: pitch + multipitch histogram + pitch histograms IISc Tonic identification Dataset Dataset: IISc Features: pitch + multipitch histogram + pitch histograms Annotation Format ---The tonic annotations are availabe both in tsv and json format. TSV: relative path to audio, tonic (Hz), Carnatic or Hindustani, artist_name, gender of the singer, vocal or instrumental JSON: name of the lead artist if available, 'filepath': relative path to the audio file, gender of the lead singer if available, 'mbid': musicbrainz id when available, 'tonic': tonic in Hz, 'tradition': Hindustani or Carnatic, 'type': vocal or instrumental where keys of the main dictionary are the filepaths to the audio files (feature path is exactly the same with a different extension of the file name).

Proyecto: //
DOI: https://doi.org/10.34810/data458
CORA.Repositori de Dades de Recerca
doi:10.34810/data458
HANDLE: https://doi.org/10.34810/data458
CORA.Repositori de Dades de Recerca
doi:10.34810/data458
PMID: https://doi.org/10.34810/data458
CORA.Repositori de Dades de Recerca
doi:10.34810/data458
Ver en: https://doi.org/10.34810/data458
CORA.Repositori de Dades de Recerca
doi:10.34810/data458

CORA.Repositori de Dades de Recerca
doi:10.34810/data45
Dataset. 2021

LIFE CYCLE ASSESSMENT OF AN INNOVATIVE SYSTEM FOR RESIDENTIAL BUILDINGS IN MEDITERRANEAN CLIMATE

  • Cabeza, Luisa F.
  • Zsembinszki, Gabriel
  • Llantoy, Noelia
  • Palomba, Valeria
  • Frazzica, Andrea
  • Dallapiccola, Mattia
  • Trentin, Federico
This dataset corresponds to a study aimed at investigating the environmental impact of an innovative system proposed for residential buildings in Mediterranean climate through a life cycle assessment. The data refer to both the innovative system and a standard reference system, which was considered for comparison purposes. Data used for a parametric study of the innovative system are also included in this dataset.

Proyecto: //
DOI: https://doi.org/10.34810/data45
CORA.Repositori de Dades de Recerca
doi:10.34810/data45
HANDLE: https://doi.org/10.34810/data45
CORA.Repositori de Dades de Recerca
doi:10.34810/data45
PMID: https://doi.org/10.34810/data45
CORA.Repositori de Dades de Recerca
doi:10.34810/data45
Ver en: https://doi.org/10.34810/data45
CORA.Repositori de Dades de Recerca
doi:10.34810/data45

CORA.Repositori de Dades de Recerca
doi:10.34810/data46
Dataset. 2021

RAW DATA ON WEIGHT AND DIET CONSUMPTION OF DIFFERENT DIETARY TREATMENTS FOR MALE AND FEMALE RATS. VALUES FOR PLASMA METABOLITE VALUES AND FOR LIVER ENZYME EXPRESSIONS

  • Oliva Lorenzo, Laia
  • Alemany, Marià, 1946-
  • Fernández López, José Antonio
  • Remesar Betlloch, Xavier
The effect of different dietary composition on liver lipid accumulation was analyzed. Diets with the same caloric content were given, but which differed in the percentage content (both in weight and derived energy) of proteins and lipids: Control diet (19% protein + 12.5% ​​lipids + 67% carbohydrates), Cafeteria diet (11% protein + 39% fat + 48% carbohydrates), Hyperlipidic diet (HF) (14% protein + 37% fat + 48% carbohydrates), hyperprotein diet (HP) (40% protein + 12% fat + 47% carbohydrates). Cafeteria and HL diets, despite having the same lipid content, differed in their lipid composition. Animals were treated for 30 days with these diets and intake was assessed. Blood and tissue samples were taken after the animals were sacrificed. The usual plasma parameters were measured and in this case, the content of cholesterol and triacylglycerols was determined in the liver, as well as the expression (RNA) of different enzymes involved in its metabolism.

Proyecto: //
DOI: https://doi.org/10.34810/data46
CORA.Repositori de Dades de Recerca
doi:10.34810/data46
HANDLE: https://doi.org/10.34810/data46
CORA.Repositori de Dades de Recerca
doi:10.34810/data46
PMID: https://doi.org/10.34810/data46
CORA.Repositori de Dades de Recerca
doi:10.34810/data46
Ver en: https://doi.org/10.34810/data46
CORA.Repositori de Dades de Recerca
doi:10.34810/data46

CORA.Repositori de Dades de Recerca
doi:10.34810/data476
Dataset. 2023

ENSEMBLE EXPRESSIVE PERFORMANCE DATASET (EEP)

  • Maestre Gómez, Esteban
  • Marchini, Marco
  • Papiotis, Panagiotis
  • Pérez Carrillo, Alfonso Antonio
The dataset contains 23 multimodal recordings of string quartet performance. Acquired data includes the audio of each performance in separate tracks: up to two ambient tracks and individual tracks acquired through contact microphones. In addition each recording includes instrumental motion capture and a set of derived instrumental bowing descriptors for each musician. The recordings were made as part of the experiments on ensemble expressive performance.

Proyecto: //
DOI: https://doi.org/10.34810/data476
CORA.Repositori de Dades de Recerca
doi:10.34810/data476
HANDLE: https://doi.org/10.34810/data476
CORA.Repositori de Dades de Recerca
doi:10.34810/data476
PMID: https://doi.org/10.34810/data476
CORA.Repositori de Dades de Recerca
doi:10.34810/data476
Ver en: https://doi.org/10.34810/data476
CORA.Repositori de Dades de Recerca
doi:10.34810/data476

CORA.Repositori de Dades de Recerca
doi:10.34810/data477
Dataset. 2023

AUTHOR PROFILING RESOURCES

  • Soler Company, Juan
El zip conté tots els recursos que s'han generat durant el desenvolupament de la tesi. Per una banda, hi ha el codi, amb el qual es poden extreure el conjunt de features tal i com es descriu a la tesi, per altre banda, hi ha també tots els datasets que s'han creat i que s'utilitzen per a tots els experiments. Utilitzant el codi, les eines externes corresponents i els datasets, es poden emular tots els experiments descrits. The zip file contains every resource that has been generated during the development of the thesis. One of the folders contains the code that is used to extract the described feature set, the other one contains every dataset that has been compiled and used in every experiment. Using the code, the external tools mentioned in the experiments and the corpora, it is possible to repeat every experiment described in the thesis.

Proyecto: //
DOI: https://doi.org/10.34810/data477
CORA.Repositori de Dades de Recerca
doi:10.34810/data477
HANDLE: https://doi.org/10.34810/data477
CORA.Repositori de Dades de Recerca
doi:10.34810/data477
PMID: https://doi.org/10.34810/data477
CORA.Repositori de Dades de Recerca
doi:10.34810/data477
Ver en: https://doi.org/10.34810/data477
CORA.Repositori de Dades de Recerca
doi:10.34810/data477

CORA.Repositori de Dades de Recerca
doi:10.34810/data478
Dataset. 2018

TIMBRE CLASSIFICATION EXPERIMENTS

  • Ó Nuanáin, Cárthach
This repository contains datasets and scripts for timbre classification experiments conducted as part the Ph.D. thesis. Two datasets were used. The first one concentrates on drum/percussion sounds while the other generalises to orchestral sounds. See the relevant iPython notebooks to re-run experiments. The orchestral sample is quite large, there is a script that pulls N number samples randomly in the folder, for performing smaller analyses. Each episode directory contains word-level and segment-level information of the whole episode and also parallel samples extracted under segments_eng and segments_spa subdirectories. Each sample is stored as an WAV audio file, text file and a CSV file containing word timing information and word-level paralinguistic and prosodic features.

Proyecto: //
DOI: https://doi.org/10.34810/data478
CORA.Repositori de Dades de Recerca
doi:10.34810/data478
HANDLE: https://doi.org/10.34810/data478
CORA.Repositori de Dades de Recerca
doi:10.34810/data478
PMID: https://doi.org/10.34810/data478
CORA.Repositori de Dades de Recerca
doi:10.34810/data478
Ver en: https://doi.org/10.34810/data478
CORA.Repositori de Dades de Recerca
doi:10.34810/data478

CORA.Repositori de Dades de Recerca
doi:10.34810/data479
Dataset. 2023

RAW DATA INFANTS' REPRESENTATION OF SOCIAL HIERARCHIES IN ABSENCE OF PHYSICAL DOMINANCE

  • Bas Villalba, Jesús Antonio
  • Sebastián Gallés, Núria
Infants' raw eye-tracker data used in the study presented at the paper entitled "Infants' representation of social hierarchies in absence of physical dominance"

Proyecto: //
DOI: https://doi.org/10.34810/data479
CORA.Repositori de Dades de Recerca
doi:10.34810/data479
HANDLE: https://doi.org/10.34810/data479
CORA.Repositori de Dades de Recerca
doi:10.34810/data479
PMID: https://doi.org/10.34810/data479
CORA.Repositori de Dades de Recerca
doi:10.34810/data479
Ver en: https://doi.org/10.34810/data479
CORA.Repositori de Dades de Recerca
doi:10.34810/data479

CORA.Repositori de Dades de Recerca
doi:10.34810/data47
Dataset. 2021

COMPARATIVE ANALYSES OF ALTERNATIVE BISCUITS MADE WITH PURPLE BARLEY FLOURS AND FRACTIONS

  • Martínez Subirà, Mariona
  • Romero Fabregat, Mª Paz
  • Puig, Eva
  • Macià i Puig, Ma Alba
  • Romagosa Clariana, Ignacio
  • Moralejo Vidal, Mª Angeles
The data reported in the dataset includes the β-glucans, arabinoxylans and phenolic compounds contents, the antioxidant capacity, the effect of baking and the physical parameters of biscuits containing different proportions of whole barley flour and pearling fractions as well as biscuits prepared with 100% refined and 100% whole wheat flour.

Proyecto: //
DOI: https://doi.org/10.34810/data47
CORA.Repositori de Dades de Recerca
doi:10.34810/data47
HANDLE: https://doi.org/10.34810/data47
CORA.Repositori de Dades de Recerca
doi:10.34810/data47
PMID: https://doi.org/10.34810/data47
CORA.Repositori de Dades de Recerca
doi:10.34810/data47
Ver en: https://doi.org/10.34810/data47
CORA.Repositori de Dades de Recerca
doi:10.34810/data47

CORA.Repositori de Dades de Recerca
doi:10.34810/data480
Dataset. 2015

CONVEX INFERENCE FOR COMMUNITY DISCOVERY IN SIGNED NETWORKS (EUROPEAN PARLIAMENT VOTING DATASET)

  • Santamaría, Guillermo
  • Gómez, Vicenç
This repository contains the necessary tools to reproduce the experiments of the paper: G. Santatmaría, V. Gómez (2015) Convex inference for community discovery in signed networks. NIPS 2015 Workshop: Networks in the Social and Information Sciences ------The method first maps the MAP problem on the Potts model as a hinge-loss minimization problem (see the paper for details). To run the code you need to install psl (included here) and if you want to additionally compare with other inference methods, such as max prod belief propagation or junction tree, you need to install the libDAI library (also included here) --------The directory europeanCongressData/ (~500 Mb) contains the votings of the EU parlament, including 300 votings events from the actual term, from May 2014 to June 2015, obtained from http://www.votewatch.eu/ * data/ : json files with the european votes * network.net : signed network built from the votes * political_parties.txt : "ground truth" party * community_results/ : results for different number of communities and initial vertices * dataComputations.py : used to build the signed network * dataProcessing.py : used to build the signed network We would appreciate if you cite the paper after using the data or the code. --------DEPENDENCIES-------- The code has been tested in Linux Mint 18.1 Serena and Ubuntu 14.04 - For PSL library, you need to have java 1.8 you may need to export JAVAHOME='/usr/lib/jvm/YOURJAVA1.8FOLDER' maven 3.x - For libDAI you will need: make doxygen graphviz libboost-dev libboost-graph-dev libboost-program-options-dev libboost-test-dev libgmp-dev cimg-dev libgmp-dev --------CODE TO RUN THE FOLLOWING EXPERIMENTS:-------- Compare the performance in terms of structural balance of max prod bp and our method against an exact inference method (junction tree), with different number of communities --------INSTALL-------- To install the experiments you have to follow the next steps: 1 Build the libdai library by doing: make -B on the folder (libdai) 2 Generate the class path of the groovy project: mvn clean install mvn dependency:build-classpath-Dmdep.outputFile=classpath.out on the psl root folder (You need to have java 1.8 and maven 3.x installed) 3 Grant exec permissions to the run.sh script --------Options-------- The main python file to run the experiments is evaluatebalanceon_sn.py. It accepts the following parameters: 1 (Int) Nodes of the graph. In order to run the junction tree we recommend to set this paremeter to 150 or less 2 (Int) The number of underlying communities 3 (Float) The maximum amount of unbalance for the experiments. We recommend 0.45 4 (Bool) Whether to use an heuristic to find the initial node for each community or to use directly random nodes from the ground truth communities. This heuristic looks alternatively for the nodes with highest negative degree and highest positive degree. For the case when the number of communities is equal to 2 (Ising Model), the heuristic is used by default. An example of execution would be: python evaluate_balance_on_sn.py 120 3 0.45 True True The results of the experiments are save in the folder results/ Scripts The main script of the hinge-loss method can be found in the folder psl/psl-example/src/main/java/edu/umd/cs/example/PottsCommunities.groovy --------For further questions, please contact vicen.gomez@upf.edu

Proyecto: //
DOI: https://doi.org/10.34810/data480
CORA.Repositori de Dades de Recerca
doi:10.34810/data480
HANDLE: https://doi.org/10.34810/data480
CORA.Repositori de Dades de Recerca
doi:10.34810/data480
PMID: https://doi.org/10.34810/data480
CORA.Repositori de Dades de Recerca
doi:10.34810/data480
Ver en: https://doi.org/10.34810/data480
CORA.Repositori de Dades de Recerca
doi:10.34810/data480

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