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FIGURE 18 in The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice
FIGURE 18. Interpretation of advertisement call differences: (A) Spectrograms and oscillograms of calls of two allopatric frog species without any significant differences (evidence for species-level divergence by molecular genetics and tadpole morphology; Vences et al. 2010a). (B) Moderate structural call differences of two allopatric populations currently assigned to the same species. The calls of Blommersia wittei from Sambava and Andrakata are composed of clicking notes of a metallic sound, whereas at Nosy Be, Benavony, and Montagne d'Ambre, notes contain pulses and calls exhibit less distinct inter-note intervals. Spectrograms produced with CoolEdit Pro at Hanning window function, 256 bands resolution.
FIGURE 16 in The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice
FIGURE 16. Spectrograms illustrating qualitative call differences between closely related species (all mantellid frogs from Madagascar). All spectrograms show only a section of a longer series of notes. Gephyromantis eiselti and G. thelenae form a clade together with a third species (Kaffenberger et al. 2011). While G. eiselti emits series of tonal notes, G. thelenae emits much slower series of much longer pulsed notes at similar temperatures. Boophis majori and B. narinsi are sister species (Wollenberg et al. 2011) and differ extremely in note duration and note repetition rate (short clicks vs. long pulsatile sounds). In both cases, the species in each pair occur in syntopy and are extremely similar to each other in adult morphology. Despite distinct qualitative call differences, genetic divergences between each of the two species pairs are remarkably low (p-distances 2.2–3.3% in a fragment of the mitochondrial 16S rRNA gene; Wollenberg & Harvey 2010; Vences et al. 2012a). In such extreme cases of bioacoustical divergence, and if the presence of different call types or recording artifacts can be excluded, bioacoustical data provide conclusive evidence for species level divergence. Recordings from Vences et al. (2006, 2012a); spectrograms made with the R package Seewave (Sueur et al. 2008a) at Hanning windowing function, 512 bands resolution.
FIGURE 9 in The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice
FIGURE 9. Example illustrating the need to consider homology aspects in terminoloy of anuran vocalizations. The calls shown are from four related species of mantellid frogs in the nominal subgenus of the genus Gephyromantis. The four species emit vocalizations consisting of a series of sound units (each corresponding to one expiration), with a defined number of units per series. All spectrograms are to scale; for G. boulengeri, an entire series is shown whereas the remaining spectrograms show parts of a series. In a note-centered terminology, one entire series would be a call, and each sound unit a note. In a call-centered terminology, in G. boulengeri, a series might be defined as one call (because no intervals of full silence occur between sound units), while in G. enki, each sound unit would be a call (separated by wide intervals of silence from the next call) and the series would be a call series. Either definition might be appropriate when looking at a single species, but in a comparative taxonomic study, it is of utmost importance to compare homologous bioacoustical entities and to apply the same name to them; hence, in a call centered approach, also the vocalization of G. boulengeri would need to be dubbed a call series. Spectrograms made with the R package Seewave (Sueur et al. 2008a) at Hanning windowing function, 512 bands resolution. Note that we here refer to homology from the perspective of sound production (one unit corresponding to one expiration) and not from the perspective of signal content of the respective sound unit.
FIGURE 12 in The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice
FIGURE 12. Nightly variation of dominant frequency (A) and call duration (B) in one individual of Leptodactylus syphax. One nocturnal activity phase of ca. 2 hrs of calling (n = 8,106 calls; 29.9 to 31.8 °C). Recording was obtained on 17 November 2014 at the Research Station 'Chiquitos', Bolivia, with a Song Meter SM2 (Wildlife Acoustics; sampling frequency 22,050 Hz; 16- bit resolution), and afterwards analyzed with software Raven Pro, version 1.4 (Bioacoustics Research Program 2011) using implemented amplitude detectors; statistics were done with R; only calls with high amplitude were considered (i.e., less intense 'introductory calls' of a series were excluded). Red lines show smoothed data (Local Polynomial Regression Fitting with span=0.05; M. Jansen & A. Masurowa, unpubl. data).
FIGURE 23 in The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice
FIGURE 23. Spectrograms and oscillograms of calls of the same individual of Bombina bombina recorded at different saturations of the recording levels and different recording distances (Tascam DR-05 digital recorder and a Sennheiser K6/ ME66 microphone; water temperature 22.1 °C; 24 May 2015 at Schorfheide-Chorin Reserve, Germany). Calls were successively recorded from the same individual within a short time period of ca. 30 minutes and each spectrogram thus shows a different call. The upper left spectrogram is from a recording with recording levels in the field deliberately set on oversaturation. The other three spectrograms were analyzed with equalized levels. Note that the number of harmonics is highest in the oversaturated recording, but also depends on recording distance, with the highest-frequency harmonics disappearing with increasing distance. Sounds of birds and insects are visible on the recordings that were not filtered to allow objective comparison. All spectrograms made with the R package Seewave (Sueur et al. 2008a), with settings: Hanning window function, 1024 bands resolution, overlap = 90%.
FIGURE 14 in The use of bioacoustics in anuran taxonomy: theory, terminology, methods and recommendations for best practice
FIGURE 14. Variation of two call traits within the Madagascar-Comoroan anuran family Mantellidae. (A) Correlation of dominant frequency and maximum male snout-vent length in 155 mantellid species. (B) Variation of note duration (mean, minimum and maximum values) among 171 species of mantellids, ordered by mean note duration (5–20 measurements per species). On Y-axis values are arranged along a logarithmic scale for graphical reasons (but scale shows original values in milliseconds, not log-transformed values). Notes defined following a note-centered scheme (cf. Fig. 7).
Accompanying simulated data for "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity"
<p>The multilevel hidden Markov model (MHMM) is a promising vehicle to investigate latent dynamics over time in social and behavioral processes. By including continuous individual random effects, the model accommodates variability between individuals, providing individual-specific trajectories and facilitating the study of individual differences. However, the performance of the MHMM has not been sufficiently explored. Currently, there are no practical guidelines on the sample size needed to obtain reliable estimates related to categorical data characteristics We performed an extensive simulation to assess the effect of the number of dependent variables (1-4), the number of individuals (5-90), and the number of observations per individual (100-1600) on the estimation performance of group-level parameters and between-individual variability on a Bayesian MHMM with categorical data of various levels of complexity. We found that using multivariate data generally alleviates the sample size needed and improves the stability of the results. Regarding the estimation of group-level parameters, the number of individuals and observations largely compensate for each other. Meanwhile, only the former drives the estimation of between-individual variability. We conclude with guidelines on the sample size necessary based on the complexity of the data and the study objectives of the practitioners.</p> <p>This repository contains data generated for the manuscript: "Go multivariate: recommendations on multilevel hidden Markov models with categorical data of varying complexity". It comprehends: (1) model outputs (maximum a posteriori estimates) for each repetition (n=100) of each scenario (n=324) of the main simulation, (2) complete model outputs (including estimates for 4000 MCMC iterations) for two chains of each repetition (n=3) of each scenario (n=324). Please note that the empirical data used in the manuscript is not available as part of this repository. A subsample of the data used in the empirical example are openly available as an example data set in the R package <a href="https://cran.r-project.org/web/packages/mHMMbayes/index.html">mHMMbayes on CRAN</a>. The full data set is available on request from the authors.</p>
Recommender Systems and AI Techniques in E-commerce: An Analysis of Trends and the Research Agenda
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Video information from the search "Deep learning" recursively on youtube through recommended videos
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Netflix Movies and TV Shows Recommendation with Neo4j
<p>Recommendation for movies can help discover new and enjoyable movies. This study uses the Neo4j Graph Database to create a recommendation system using the Netflix Movie Dataset. The objective of this research is the development of a movie recommendation algorithm using the k-NN similarity algorithm and FastRP node embedding machine learning. The results have provided recommendations based on similar attributes, such as actors, directors, country, type, and rating.</p>
Empowering Coffee Farming Using Counterfactual Recommendation based RNN-IoT Integrated Soil Fertility Control System
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Alarm management in provisional COVID-19 intensive care units: a retrospective analysis and recommendations for future pandemics
<p>The clinical audit logs were manually collected from the patient monitoring system of four intensive care units (ICU) from a large German hospital via USB stick from the central patient monitoring device. The data consists of the time, bed number, alarm type (i.e., parameter, device, alarm criticality) and alarm handling (e.g., threshold adjustments, use of the pause function). No actual patient identifying data elements were collected. For further deidentification, dates were shifted into the future by a pseudo-random offset for all patients; the bed number was replaced by a pseudonym. Day and night rhythm, weekends, the season and the bed characteristic (double room, single room) were not affected by this process.</p> <p> </p>
A Quic(k) Security Overview: A Literature Research on Implemented Security Recommendations
<p>Contains additional material and the slideset for the ARES 2023 paper <a href="https://dl.acm.org/doi/10.1145/3600160.3605164" rel="nofollow">A Quic(k) Security Overview: A Literature Research on Implemented Security Recommendations</a>.</p>
Data from: drones as a tool to study and monitor endangered Grey Crowned Cranes (Balaerica regulorum): behavioural responses and recommended guidelines
<p>These data detail the results of an investigation into the impact of drones and on-foot approaches on the behaviour of the endangered Grey Crowned Crane (<em>Balearica regulorum</em>). In total, 313 drone flights and 56 on-foot approaches were conducted over three different Grey Crowned Crane group types - pairs (110 flights, 26 on-foot), families (66 flights, 7 on-foot), and flocks (110 flights, 23 on-foot). Response data describe the number of birds exhibiting a particular behaviour (1 - no behaviour change, 2 - heads raised to observe surroundings, 3 - wings raised, 4 -moving away, and 5 - flying away) based on a photograph taken during the approach. Predictor data include the distance between the drone or on-foot observer and the bird grouping and a description of the group type. The number of individuals in the group can be inferred from the response data.</p>
Processed KuaiRand-1K dataset for the paper: Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework
<p>The original public dataset is published in https://zenodo.org/records/10439422, we processed the KuaiRand-1K dataset for the paper: Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework.</p>
Supplemental package of a study on Microservices versus Monoliths: Identifying Challenges and Proposing Practical Recommendations
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Research integrity in instructions for authors in Japanese medical journals using ICMJE recommendations: A descriptive literature study
<p>The goals of this project were to compare research integrity content in Instructions for Authors in ICMJE member journals with those in the English- and Japanese-language journals of the Japanese Association of Medical Sciences (JAMS).</p> <p>Therefore, this dataset contents include the following three categories: 1) journals' background information, 2) description numbers of research integrity topics, and 3) journal numbers that required ICMJE description forms in ICMJE member journals, English- and Japanese-language journals.</p>
Artfiact for the Proc. ACM Softw. Eng. article "Sharing Software-Evolution Datasets: Practices, Challenges, and Recommendations."
<p>This dataset is a collection of all notes taken for the article:</p> <p> David Broneske, Sebastian Kittan, and Jacob Krüger:<br> Sharing Software-Evolution Datasets: Practices, Challenges, and Recommendations. <br> Proc. ACM Softw. Eng. 1, FSE, 2024.<br> https://doi.org/10.1145/3660798</p> <p>Please refer to the readme for a description of the files involved in the zip file.</p>
Personalize E-Commerce Product Recommendations Based on User Behavior Using Reinforced Learning Algorithms
<p><span>The development of a personalized and adaptive e-commerce product recommendation system will be developed using the Reinforcement Learning algorithm in this study. Initial data is extremely promising in its ability to raise sales conversion: 30% of the products added to the cart are never purchased. Additionally, there is a strong correlation of 0.8 between viewed versus purchased products. Data collection was from 447 Indonesian respondents over a period of June to July 2024. It was collected using an online questionnaire that measures recommendation quality, satisfaction, and ease of use with purposive sampling. Partial Least Squares Structural Equation Modeling was done on the data analysis. From that, it has been found that system quality is positively related to the accuracy, novelty, and diversity of the recommendation. The results further show how this would lead to an improved user experience, satisfaction, and sales conversion with the reinforcement learning-based system. These findings give insight into developing efficient adaptive recommendation systems on e-commerce platforms and open opportunities for further research. </span></p>
Creating a dataset on fertilizers and fertilization recommendations
<p><span>Within the scope of WP3 T 3.2 </span><span>to determine yield responses to lower fertilization rates crop-specific N fertilizer amounts applied or recommended by countries for important agricultural crops were needed. In this context, FAOSTAT, Eurostat and IFASTAT databases were examined to access N fertilization amounts. These databases usually provide nitrogen fertilizer amounts for all agricultural production, regardless of crop. In addition, for some countries, fertilizer quantities by crop needed were not included (e.g. wheat, maize). For this reason, the national coordinator of each partner country of EJP SOIL was contacted to request the recommended amounts of N fertilizers for important crops in their country and their long-term yield values. 15 European countries (Austria, Germany, Netherlands, Belgium, Norway, Sweden, Switzerland, Hungary, Finland, Spain, Portugal, Poland, Latvia, UK and Turkey) provided these data. <span>To estimate yields response to reduced fertilization an approach was created and used by bringing together data from various sources. </span>The yields estimation was performed for –20% reductions in N fertilization for selected important crops which are wheat, maize, barley, sugarbeet, potato and rapeseed for 38 European countries listed in below excel sheet including Switzerland, Türkiye and UK . This approach also draws on the previously reviewed LTEs meta-analysis by Hijbeek et al. (2007) (with support of SOMMIT Project) and van Grinsven et al. (2022). As a result, considering FAOSTAT (2023) yield data, Country N fertilization data, Hijbeek et al. (2017) and van Grinsven et al. (2022) changes in yield for a 20% reduction in N fertilization rates for important crops were calculated for the Countries. <span>For the rapeseed evaluation, FAOSTAT (2001-2022) mean yield data and N recommendation values of country datasets were used and the final estimations were calculated using Tian et al. (2023) equation. If yield reduction cannot be estimated from the above data for other European countries, matching was performed according to the pediclimatic zonation described in Toth et al. (2017).<span> </span></span></span></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.