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opencc-by-4.0Jun 2022View details →

Global terrestrial water storage reconstruction using cyclostationary empirical orthogonal functions (1979 - present)

The dataset consists of a 1979-present reconstruction of Terrestrial Water Storage (TWS) anomalies from Gravity Recovery and Climate Experiment (GRACE) using common modes of variability between TWS and terrestrial precipitation and land surface temperatures.

opencc-zeroJul 2022View details →

Data for empirical example in: An effect size for comparing the strength of morphological integration across studies

Understanding how and why phenotypic traits covary is a major interest in evolutionary biology. Biologists have long sought to characterize the extent of morphological integration in organisms, but comparing levels of integration for a set of traits across taxa has been hampered by the lack of a reliable summary measure and testing procedure. Here we propose a standardized effect size for this purpose, calculated from the relative eigenvalue variance, Vrel. First we evaluate several eigenvalue dispersion indices under various conditions, and show that only Vrel remains stable across samples size and the number of variables. We then demonstrate that Vrel accurately characterizes input patterns of covariation, so long as redundant dimensions are excluded from the calculations. However, we also show that the variance of the sampling distribution of Vrel depends on input levels of trait covariation, making Vrel unsuitable for direct comparisons. As a solution, we propose transforming Vrel to a standardized effect size (Z-score) for representing the magnitude of integration for a set of traits. We also propose a two-sample test for comparing the strength of integration between taxa, and show that this test displays appropriate statistical properties. We provide software for implementing the procedure, and an empirical example illustrates its use.

opencc-by-4.0Jul 2022View details →

Probabilistic forecasts of the daily maximum of the Kp index produced by the SERENADE prototype model and three empirical models for the period 2010-2018

This dataset contains the probabilistic outputs of SERENADE's first prototype model dedicated to the forecasting of the \(\textit{Kp}_{\textrm{max, 24 h}}\) index for forecasting horizons ranging between 2 and 7 days. The period covered is the one of the SDOML dataset, which is 2010-05 --- 2018-12. All data is contained in a single pickle file, that can be opened in Python, using the following code lines: \(\texttt{import pickle}\\ \texttt{with open(DATA_PATH+`/serenade_outputs.pkl', `rb') as f:}\\ ~~~~\texttt{dict_outputs = pickle.load(f)}\) The pickle file contains a dictionnary, which itself contains Pandas DataFrames. Each DataFrame corresponds to a forecasting horizon. The dictionnary's keys are the forecasting horizons stored as strings, that is: \(\texttt{dict_output.keys() = [`2',`3',`4',`5',`6',`7']}\) The DataFrames are indexed by datetime. They contain the observed (true) hourly values of the daily maximum of the Kp index, the forecasts provided by SERENADE and three baseline models (Climatology model, Persistence model and 27-day Recurrence model). The forecast values include the mean and the standard deviation of the forecast normal distributions. Missing moments are due to the absence of EUV images needed to provide the forecast at the given moment.

opencc-by-4.0Nov 2023View details →

An Empirical Evaluation of Unsupervised Event Log Abstraction Techniques in Process Mining

This upload contains the event logs, generated by L-Sim, on which the experiments of the related paper were performed.The related paper is accepted in the journal Information Systems.

opencc-zeroAug 2022View details →

Supplementary material and supplementary data files for: Handling logical character dependency in phylogenetic inference: Extensive performance testing of assumptions and solutions using simulated and empirical data

Logical character dependency is a major conceptual and methodological problem in phylogenetic inference of morphological datasets, as it violates the assumption of character independence that is common to all phylogenetic methods. It is more frequently observed in higher-level phylogenies or in datasets characterizing major evolutionary transitions, as these represent parts of the tree of life where (primary) anatomical characters either originate or disappear entirely. As a result, secondary traits related to these primary characters become "inapplicable" across all sampled taxa in which that character is absent. Various solutions have been explored over the last three decades to handle character dependency, such as alternative character coding schemes and, more recently, new algorithmic implementations. However, the accuracy of the proposed solutions, or the impact of character dependency across distinct optimality criteria, has never been directly tested using standard performance measures. Here, we utilize simple and complex simulated morphological datasets analyzed under different maximum parsimony optimization procedures and Bayesian inference to test the accuracy of various coding and algorithmic solutions to character dependency. This is complemented by empirical analyses using a recoded dataset on palaeognathid birds. We find that in small, simulated datasets, absent coding performs better than other popular coding strategies available (contingent and multistate), whereas in more complex simulations (larger datasets controlled for different tree structure and character distribution models) contingent coding is favored more frequently. Under contingent coding, a recently proposed weighting algorithm produces the most accurate results for maximum parsimony. However, Bayesian inference outperforms all parsimony-based solutions to handle character dependency due to fundamental differences in their optimization procedures—a simple alternative that has been long overlooked. Yet, we show that the more primary characters bearing secondary (dependent) traits there are in a dataset, the harder it is to estimate the true phylogenetic tree, regardless of the optimality criterion, owing to a considerable expansion of the tree parameter space.

opencc-by-4.0Dec 2021View details →

A Large-Scale Empirical Study of Android Sports Apps in the Google Play Store

This repository contains the dataset for our study "A Large-Scale Empirical Study of Android Sports Apps in the Google Play Store" and this will help to replicate our study, also the <a href="https://github.com/mooselab/Sports-Apps-Analysis">replication package</a> to direct you to help replicate it for your dataset too.  Note: The dataset given are protected with password, and the password is available in our published paper

opencc-by-4.0Oct 2022View details →

Can Public Transport Improve Accessibility for the Poor Over the Long Term? Empirical Evidence in Paris, 1968-2010

This dataset allows to reproduce the results of the paper "Can Public Transport Improve Accessibility for the Poor Over the Long Term? Empirical Evidence in Paris, 1968-2010", by Vincent Viguié, Charlotte Liotta, Basile Pfeiffer, and Nicolas Coulombel, submitted to the Journal of Transport Geography and available at SSRN: <a href="https://ssrn.com/abstract=4049765">https://ssrn.com/abstract=4049765</a> or <a href="https://dx.doi.org/10.2139/ssrn.4049765">http://dx.doi.org/10.2139/ssrn.4049765</a>. Files MODUS_private_cars.csv and MODUS_public_transport.csv correspond to the average transport time between municipalities by public transit for the Census years between 1968 and 20109, and by car for the year 2010. MODUS is a model calibrated by the public regional road and transport authority (DRIEAT Île de France) to simulate road traffic and transit in the region. More details can be found in the research paper. Files COM_RES_csp_1968_2010.csv and COM_EMP_csp_1968_2010.csv correspond to the number of employed workers, by place of residence or employment, at the municipality (communes) level, with stable geographical boundaries over time. They are derived from the detailed census of the French population carried out by the INSEE, the French national statistical institute. More details can be found in the research paper.

opencc-zeroOct 2022View details →

Data from: Can extreme climatic events induce shifts in adaptive potential? A conceptual framework and empirical test with Anolis lizards

Multivariate adaptation to climatic shifts may be limited by trait integration that causes genetic variation to be low in the direction of selection. However, strong episodes of selection induced by extreme climatic pressures may facilitate future population-wide responses if selection reduces trait integration and increases adaptive potential (i.e., evolvability). We explain this counter-intuitive framework for extreme climatic events in which directional selection leads to increased evolvability and exemplify its use in a case study. We tested this hypothesis in two populations of the lizard Anolis scriptus that experienced hurricane-induced selection on limb traits. We surveyed populations immediately before and after the hurricane as well as the offspring of post-hurricane survivors, allowing us to estimate both selection and response to selection on key functional traits: forelimb length, hindlimb length, and toepad area. Direct selection was parallel in both islands and strong in several limb traits. Even though overall limb integration did not change after the hurricane, both populations showed a non-significant tendency toward increased evolvability after the hurricane despite the direction of selection not being aligned with the axis of most variance (i.e., body size). The population with comparably lower between-limb integration showed a less constrained response to selection. Hurricane-induced selection, not aligned with the pattern of high trait correlations, likely conflicts with selection occurring during normal ecological conditions that favor functional coordination between limb traits, and would likely need to be very strong and more persistent to elicit a greater change in trait integration and evolvability. Future tests of this hypothesis should use G-matrices in a variety of wild organisms experiencing selection due to extreme climatic events.

opencc-by-4.0Apr 2024View details →

State of Practice and Challenges of Issue Management for Component-based and Service-Oriented Systems: An Empirical Study

Modern software systems often consist of independently developed components, e.g., libraries or (micro-)services, that can be combined to form a larger architecture. Many of these components are developed externally, i.e., in other projects by other teams, which is particularly the case in service-oriented architectures. Even though the components are independently developed, bugs may arise that propagate along the call chains, which sometimes negatively affect the calling components. However, as such components are typically managed in separate issue management systems (IMS), identifying that a downstream component is affected by an upstream component's issues is complex and time-consuming. Even though some scientific works and IMS forums discuss how to manage such cross-component issues, there is no systematic study on the state of practice and the challenges of issue management when different components are affected. Therefore, this study aims to determine which types of components are usually included in modern software projects, how developers identify and manage issue propagation between components, and how often they face such propagations. To get these insights, we conducted an empirical study through a questionnaire with 64 industry experts and open-source contributors and interviewed seven of them. Our key takeaways help researchers and software engineers to understand possible impacts and to improve cross-component issue management. We identified, for example, that related issues currently are non-semantically linked via URLs in issue comments.

opencc-by-4.0Apr 2024View details →

Game Data Event Log from Age of Empire Interactions

The event log describes players' behavior in the real-time strategy game Age of Empires. Each case describes the events that a player triggers in a game. There are 185.094 cases that consist of more than 18 million events. The timestamp represents the elapsed time since the start of the game. Each player is assigned an Elo ranking that is higher, the better the player is. This allows us to study the implications of skill on players' behavior. Also, games can take place on different maps, influencing the situations the players find themselves in. Some games follow clear initial strategies, which are called build orders. These build orders are comparable to chess openings. The event log is split into ten parts to make the import feasible for smaller machines.

opencc-zeroJun 2024View details →

Data from: Empirical verification of feeding selectivity of larval and juvenile pelagic fishes using in situ zooplankton communities

Most studies on the feeding ecology of larvae and juveniles of commercially important pelagic fishes have used field-based approaches. However, due to possible biases related to net sampling, it is uncertain whether the results obtained from those studies truly represent the situation of live fish in the sea. Here we investigated the feeding ecology of pelagic fishes through a laboratory experiment minimizing the biases inherent in field net sampling. In the experiment, hatchery-reared juvenile chub mackerel (Scomber japonicus) and larval/juvenile Japanese anchovy (Engraulis japonicus) were fed with wild-caught zooplankton assemblages collected from around Hakatajima Island in the Seto Inland Sea, Japan. The relationships between fish size and prey number in the gut, and the selectivity on each prey organism were determined. As a result, in both species, prey number and size increased with body size, and the fish showed strong selectivity for crustaceans including copepodites and adults of copepods. Our data has also clearly indicated that both species can selectively prey on preferred foods that are rare while avoiding non-preferred foods that are abundant. These results, which substantially accord with reports from previous field studies, will not only help field scientists make a convincing interpretation of their data, but also open the possibility of further laboratory studies on detailed mechanisms of the feeding selectivity of larval/juvenile pelagic fishes.

opencc-by-4.0Jul 2023View details →

Technical Debt Tools: a Survey and an Empirical Evaluation

Background: The life cycle of a technical debt from its identification to its payment is long and may include several activities, such as identification and management. There is a lot of research in the literature to address different sets of these activities by different means. Specifically, several tools have already tackled such technical debt identification problem. However, only a few studies empirically assessed those tools. Method: In this article, we carried a multi- method research. We first surveyed the literature for the technical debt tools available an then we evaluated two of them, which aim at identification of self-admitted technical debt. Thy are named eXcomment e DebtHunter. Results: We found 92 tools employing different approaches to support technical debt life cycle management. Most of them (59%) address only the high level task of management, instead of actually identify and pay the debt. Additionally, as for our empirical evaluation of tools, our results show that DebtHunter found only 7% of debt identified by eXcomment. In the other way around, eXcomment found 19.9% the debt find by DebtHunter. Besides, both tools have low levels of precision and recall. Conclusion: It is hard to find technical debt through comments. Both tools can find indicators of debt items, however they struggle on the precision and recall. In fact, although eXcomment and DebtHunter diverge on the amount of debt identified, they seem to converge with regard to the type o debt present in the system under evaluation.

opencc-by-4.0Jun 2024View details →

Solutions for Reproducibility in Empirical Research: Virtual Machines, Containers, Environment Management Packages, and Cloud Platforms

This image provides a comprehensive overview of various technologies and platforms used to enhance the reproducibility of empirical research. It is divided into several sections: <ol> <li>Virtual Machines (VMs): the left section of the image illustrates the architecture of VMs with Type 1 and Type 2 hypervisors.     - Type 1 Hypervisor runs directly on the hardware, providing high efficiency and performance. Examples include VMware ESXi, Microsoft Hyper-v, and Xen Project.    - Type 2 Hypervisor runs on an existing operating system, offering flexibility at the cost of some performance. Examples include Oracle VirtualBox, VMware Workstation, and Parallels.</li> <li>Containers: the middle section of the image explains the containerization concept, which shares the host operating system's kernel, making containers more lightweight than VMs. Technologies like Docker and Kubernetes are shown as popular solutions for container orchestration.</li> <li>Environment Management Packages: the top right section focuses on tools for managing software dependencies and environments. renv (for R) and Conda (for Python and other languages) are highlighted as key tools for creating reproducible research environments.</li> <li>Cloud Platforms: the bottom right section features various cloud-based platforms that facilitate reproducible research by providing scalable and shareable computational environments. Platforms include Google Colab, Posit Cloud, JupyterHub, Binder, Nextjournal, OpenShift, and Code Ocean.</li> </ol> Together, these solutions provide a robust framework for ensuring that empirical research can be reliably reproduced and validated by others, addressing the challenges of dependency management, environment consistency, and computational resource availability.

opencc-zeroJun 2024View details →

Dataset: Magic Empire Global Limited (MEGL) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-by-4.0Jul 2024View details →

Data from an empirical study on generative artificial intelligence painting

This is an empirical study on generative artificial intelligence painting, including research methods, basic data of 17 subjects and their AI art painting, and quantitative data after their data analysis.

BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 5. PSD (dB/Hz) vs freaquency (Hz) of each IMF showen in fig 4 in channel C4 (a) and in C3 (b)

In Fig 5, we noted that ocular artifact frequency is generally low around 5Hz with high amplitude. This artifact appears mainly in IMF3 and IMF4. Finally, band power was applied for the new signal. As a last step, the logarithm of the BP is calculated in order to transform the distribution of this feature to a more Gaussian like shape, because the classifiers we used, such as HMMs and SVM assume normally distributed features.

BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 4. The EMD decomposition results for subject 2 when he imagines left hand movement

Fig. 4 shows the EMD decomposition result of one-trial (left hand movement imagination) for subject 2 in the channels C3 and C4 respectively (the pre-filtered EEG signal used for this illustration is not corrupted by blinking artifact.). Each channel is decomposed into ten IMFs and one residue

BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 5b. PSD (dB/Hz) vs freaquency (Hz) of each IMF showen in fig 4 in channel C4 (a) and in C3 (b)

Therefore, the new signal is reconstructed by keeping only the two first IMFs. EMD also allows eliminating the artifacts in the EEG during the recording sessions like eye blinks and eyeball movements. In Fig 5, we noted that ocular artifact frequency is generally low around 5Hz with high amplitude. This artifact appears mainly in IMF3 and IMF4. Finally, band power was applied for the new signal. As a last step, the logarithm of the BP is calculated in order to transform the distribution of this feature to a more Gaussian like shape, because the classifiers we used, such as HMMs and SVM assume normally distributed features.

BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 3. Hybrid EMD-BP approach for one trail feature extraction

In this work, we propose a direct nonlinear approach to extract the more relevant IMFs corresponding to the different frequency components in the  and  bands and then obtain the BP in order to use them as features for mental task classification (see Fig. 3). The feature vector p used for the demonstration in this paper is composed, for each sample I, 1

BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 4b. The EMD decomposition results for subject 2 when he imagines left hand movement

d et al., 2011). Fig. 4 shows the EMD decomposition result of one-trial (left hand movement imagination) for subject 2 in the channels C3 and C4 respectively (the pre-filtered EEG signal used for this illustration is not corrupted by blinking artifact.). Each channel is decomposed into ten IMFs and one residue.