6,048 research outputs found
astromatt42/digb_sfgs: Release for 10.21203/rs.3.rs-106679/v1
No full textThis release was used to compute the results in https://doi.org/10.21203/rs.3.rs-106679/v1
For any queries please contact the corresponding author
#nowplaying-rs
No full text<p>The nowplaying-rs dataset features context- and content features of listening events. It contains 11.6 million music listening events of 139K users and 346K tracks collected from Twitter. The dataset comes with a rich set of item content features and user context features, as well as timestamps of the listening events. Moreover, some of the user context features imply the cultural origin of the users, and some others - like hashtags - give clues to the emotional state of a user underlying a listening event.</p>
<p>The dataset contains three files:</p>
<ul>
<li>user_track_hashtag_timestamp.csv contains basic information about each listening event. For each listening event, we provide an id, the user_id, track_id, hashtag, created_at </li>
<li>context_content_features.csv: contains all context and content features. For each listening event, we provide the id of the event, user_id, track_id, artist_id, content features regarding the track mentioned in the event (instrumentalness, liveness, speechiness, danceability, valence, loudness, tempo, acousticness, energy, mode, key) and context features regarding the listening event (coordinates (as geoJSON), place (as geoJSON), geo (as geoJSON), tweet_language, created_at, user_lang, time_zone, entities contained in the tweet).</li>
<li>sentiment_values.csv contains sentiment information for hashtags. It contains the hashtag itself and the sentiment values gathered via four different sentiment dictionaries: AFINN, Opinion Lexicon, Sentistrength Lexicon and vader. For each of these dictionaries we list the minimum, maximum, sum and average of all sentiments of the tokens of the hashtag (if available, else we list empty values). However, as most hashtags only consist of a single token, these values are equal in most cases. Please note that the lexica are rather diverse and therefore, are able to resolve very different terms against a score. Hence, the resulting csv is rather sparse. The file contains the following comma-separated values: <hashtag, vader_min, vader_max, vader_sum,vader_avg, afinn_min, afinn_max, afinn_sum, afinn_avg, ol_min, ol_max, ol_sum, ol_avg, ss_min, ss_max, ss_sum, ss_avg >, where we abbreviate all scores gathered over the Opinion Lexicon with the prefix 'ol'. Similarly, 'ss' stands for SentiStrength. </li>
</ul>
<p>Please note that user_track_hashtag_timestamp.csv and context_content_features.csv partly provide the same features. We deliberately chose to do so to be able to provide useable files that do not have to be matched and joined with each other to perform e.g., simple recommendation tasks.</p>
<p>Please also find the training and test-splits for the dataset in this repo. Also, Asmita provides prototypical implementations of a context-aware recommender system based on the dataset at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM.</p>
<p><br>
If you make use of this dataset, please cite the following paper where we describe and experiment with the dataset:</p>
<p>@inproceedings{smc18,<br>
title = {#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems},<br>
author = {Asmita Poddar and Eva Zangerle and Yi-Hsuan Yang},<br>
url = {http://mac.citi.sinica.edu.tw/~yang/pub/poddar18smc.pdf},<br>
year = {2018},<br>
date = {2018-07-04},<br>
booktitle = {Proceedings of the 15th Sound & Music Computing Conference},<br>
address = {Limassol, Cyprus},<br>
note = {code at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM},<br>
tppubtype = {inproceedings}<br>
}</p>
Residual brain injury after early discontinuation of cooling therapy in mild neonatal encephalopathy
No full textConverter USB/RS 485
No full textThis thesis is describing problematic of realisation of converter from USB type media into the universal RS-485 bus which is mainly used for the industrial applications (author is using frequently as a device in order to enable communication between server and RFID devices). This thesis contains theoretical information, realisation of the device itself and assesment of reached targets
Converter USB/RS 485
No full textThis thesis is describing problematic of realisation of converter from USB type media into the universal RS-485 bus which is mainly used for the industrial applications (author is using frequently as a device in order to enable communication between server and RFID devices). This thesis contains theoretical information, realisation of the device itself and assesment of reached targets
Voxelwise rs-fMRI representation learning: A non-linear variational approach
No full textResting-state fMRI (rs-fMRI) has become an important imaging modality and is commonly used to study intrinsic brain networks. These networks can be obtained by decomposing rs-fMRI data into components, using independent component analysis (ICA). Recently, these ICA components have been used as inputs for neural networks to learn complex relations between the intrinsic networks of the brain and mental disorders or demographic variables. Instead of training a non-linear classifier on these linearly decomposed components, this work asks whether unsupervised representation learning can lead to linearly separable representations for multiple downstream tasks. We propose to apply non-linear representation learning to voxelwise rs-fMRI data. Learning the non-linear representations is done using two versions of a variational autoencoder (VAE). The first version is a vanilla VAE with 3D residual blocks in both its encoder and decoder. The second version is based on the identifiable VAE and uses a time-dependent prior. The models train to reconstruct the original input data from latent variables it infers. Three predictive models then evaluate the predictive power of the latent variables on an age regression, a sex classification, and a schizophrenia classification task. Each of the predictive models performs predictions for each of the three tasks. The predictive models are a support vector machine (SVM), a k-nearest neighbor (k-NN) model, and a long short-term memory (LSTM) neural network.We show that our method performs exceptionally well on the age regression and sex classification tasks without any supervision. These results imply that VAEs can model predictive variations in their latent spaces for demographic variables. The models, however, do not do well on the schizophrenia classification task, even when the models are pretrained. Despite the lower performance on the schizophrenia classification task, the overall results are encouraging and pave the way for future work on voxelwise representation learning.Electrical Engineering | Embedded SystemsBiomedical Engineerin
СРАВНИТЕЛЬНАЯ ХАРАКТЕРИСТИКА ИЗДАНИЙ РОМАННОГО ТВОРЧЕСТВА МИР ДЖАЛАЛА
No full textIn the article, the author of advanced ideas, explores published copies of novelist Mir Jalal's novels "The Resurrection Man (1936)", "The Open Book (1945)", "People of the Same Age,1948", "The New City (1951)", "Where are we going” (1957) comparative analysis. The repeated publication of the novels of the Soviet in the Soviet era or in the modern era, always proves the relevance of the talented creator. Two of the five novels of Mir Jalal, the one we talked about, have been the subject of past and the third one.In the article, the author of advanced ideas, explores published copies of novelist Mir Jalal's novels "The Resurrection Man (1936)", "The Open Book (1945)", "People of the Same Age,1948", "The New City (1951)", "Where are we going” (1957) comparative analysis. The repeated publication of the novels of the Soviet in the Soviet era or in the modern era, always proves the relevance of the talented creator. Two of the five novels of Mir Jalal, the one we talked about, have been the subject of past and the third one
Modeling a variable surface resistance (rs) for alfalfa and assessing the ASCE rs performance in the reference evapotranspiration equation
No full text2016 Fall.Includes bibliographical references.Accurate quantification of crop water requirement is necessary for proper irrigation water management. The knowledge of actual crop evapotranspiration (ETc) is important and is necessary for estimating irrigation water requirements. The most common procedure of obtaining actual crop evapotranspiration (ETc) is by first calculating the reference crop evapotranspiration (ETr) and then multiplying it with the appropriate crop coefficients (Kc). If the surface resistance (rs) of a particular crop can be modeled, then ETc can be directly calculated without using Kc. The overall objectives of this dissertation were to model surface resistance for alfalfa reference crop and to find an effective value of the surface resistance of alfalfa in the ASCE Standardized Reference ET equation. It has been found that using a single Kc curve for different climatic conditions can lead to significant error in estimating ETc. Hence it is important to find appropriate Kc for different crops for local climatic condition. Lysimeters are generally used to determine the values of Kc, as lysimetry is considered a reliable method of quantifying the ET losses from a control volume. This study found that using lysimeter ET data to obtain Kc can be problematic especially when the field is heterogeneous. In order to develop Kc for various crops, it is recommended to use some years of reliable data with uniform healthy and unstressed crop surface conditions both inside and outside the lysimeter. This study was focused on to develop a model for surface resistance (rs) of alfalfa in order to calculate alfalfa ETc in a one-step approach without the need for Kc values. Surface resistance was estimated by inverting the aerodynamic equation using ET measured from lysimeter and sensible heat flux (H) measured from large aperture scintillometer (LAS). This observed rs showed a very good correlation with leaf area index (LAI) and crop height (hc). The alfalfa rs was then modeled as a function of LAI and hc (which is referred to as rs(LAI) and rs(hc) respectively). Then these modeled rs s were incorporated into the Penman Monteith (PM) equation to estimate alfalfa hourly ET, which performed very well when compared with the measured hourly lysimeter ET. The conventional alfalfa rs, developed by Allen et al. (1989) was found to underestimate rs significantly especially when the crop height was short (less than 25 cm). It was found that ET_conventional_rs was not applicable to estimate alfalfa ET when the crop height was less than 25 cm. The modeled rs(LAI) and rs(hc) are constant throughout the day, but in reality, rs changes throughout the day. Hence hourly variable rs was also developed based on aerodynamic resistance (ra), canopy temperature (Tc) and vapor pressure deficit (VPD). It was found that PM equation incorporating the hourly variable rs improved the alfalfa ET estimation when compared with the conventional rs approach. ASCE-EWRI Standardized Reference ET for tall reference crop was found to underestimate measured ET by about 10 per cent. The equation assumes the value of rs for alfalfa as 30 s/m. When the value of rs was changed from 30 s/m to 10 s/m, the performance of the equation improved, resulting in no bias and root mean square error (RMSE) reduction from 0.08 mm/h (15.3%) to 0.06 mm/h (11.4%) in 2009 and from 0.09 mm/h (14.1%) to 0.06 mm/h (10.1%) in 2010
Developing a decision support tool for the operation of parallel AS/RS during partial downtime: A case study at Jumbo Supermarkets
No full textThis paper investigates the optimisation of Automated Storage and Retrieval Systems (AS/RS) in warehousing by minimising performance losses during partial downtime. Given the increasing automation in logistics, AS/RS systems play a pivotal role, yet the operation of those systems during partial downtime remains a topic ignored in literature. This research fills this gap by exploring the effects of partial downtime in AS/RS through a reusable Discrete Event Simulation model which was developed in Python. This model incorporates the influence of both upstream and downstream systems, a characteristic notably absent from the limited number of publicly-available AS/RS models. Collaborating with Jumbo Supermarkets, the study utilises their highly automated distribution centre with an Order Consolidation Buffer housing 4 dual-crane AS/RS units as a case study. The study identifies operational policies to mitigate partial downtime effects, developed for scenarios with one or both cranes down within an AS/RS. Results suggest strategic workload distribution adjustments among AS/RS can significantly reduce performance degradation, particularly during high workload periods. After comparing both scenarios, it was concluded that for most scenarios, it is beneficial to keep operating the remaining crane when a crane breaks down, even though this slows down repairs. Overall, this research offers insights into parallel AS/RS dynamics under partial downtime and provides practical guidelines for effective operations.Mechanical Engineering | Multi-Machine Engineerin
Improving the performance of distributed conceptual hydrological models using the spatio-temporal patterns of RS observations: Improving the performance of distributed conceptual hydrological models using the spatio-temporal patterns of RS observations
No full textHydrological models are used for all kinds of water management applications. Detailed hydrological simulations are needed to solve the hydrological problems of the 21st century, especially in developing countries. However, sufficient hydrological and meteorological data is often not available. The use of remote sensing (RS) datasets may offer a solution to this problem. RS datasets can perfectly be applied in distributed conceptual hydrological models. In this study, several RS datasets are applied in the calibration of a distributed conceptual hydrological model, and the influence of this approach on the overall model performance is assessed. The RS data applied in this study include terrestrial water storage anomaly (TWSA) data, normalized difference vegetation index (NDVI) data, and soil moisture (SM) data. Also the input and forcing data for the hydrological model consists of datasets based on satellite observations. This data is used in a wflow hbv model, which is applied to the Volta basin in Western Africa as a case-study. In this study, not only the effect of including RS data in the calibration of a distributed hydrological model on streamflow is assessed, but also the effect on a set of internal components of the system, directly related to the datasets used for calibration. These internal stocks and fluxes are the TWSA, the actual evapotranspiration (AET) and the amount of soil moisture in the unsaturated zone. Together with streamflow, the assessment of these stocks and fluxes make up the overall model performance of the system. The effect on the overall model performance is examined using different scenarios, in which different combinations of datasets are used for calibration. Not the absolute values, but the spatiotemporal patterns of the remote sensing datasets are used for model assessment. This is done using the spatial pattern efficiency metric (ESP ). Model optimization was done using the Dynamically Dimensioned Search (DDS) algorithm. The results show that the hydrological model developed for this case-study is already able to simulate streamflow and the temporal patterns of the RS datasets quite well, when it is calibrated on streamflow only. However, the spatial pattern representation of the RS datasets was found to be inadequate and the differences in streamflow simulation performance for the different subcatchments is large. When SM or TWSA data was added to the calibration procedure, the temporal and spatial pattern representations only changed minimally, which is attributed to limited model complexity and flexibility. However, generally a trade-off effect was observed in which the spatial and temporal pattern representation improved, but the streamflow performance decreased. This effect was stronger for the addition of the SM dataset to the calibration than for the addition of TWSA dataset. Although there is definitely a strong connection between NDVI and AET, the physical relation between the two variables was found to be too weak to be used for hydrological model calibration, even when only the spatial and temporal pattern information was used. The overall model performance did improve most in the calibration catchments in the scenario in which Q, SM and TWSA data were combined in the calibration procedure, but the differences with the baseline scenario were only small. For the streamflow performance however, the differences between the scenarios are quite significant. It was shown that calibrating a hydrological model on the spatial and temporal patterns of RS data only (non-Q calibration) can accurately represent the temporal pattern of streamflow observations, but not the magnitude of the flow values. It is recommended to repeat this study using a more complex and more flexible model setup, which allows the model to use the freedom it is given to better represent the spatial patterns observed with RS.Water Managemen
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