University of Stirling
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The Cartography of Computational Search Spaces
No full textThe dataset contains landscape data for "Mapping the global structure of TSP fitness landscapes", G. Ochoa, N. Veerapen, Journal of Heuristics, 2017. The dataset describes the network structure of the local optima networks for Traveling Salesman Problem instances that are sampled using Chained Lin-Kernighan. Dedicated UnZip software is recommended for accessing the dataset, for example, IZArc.The dataset contains landscape data for "Mapping the global structure of TSP fitness landscapes", G. Ochoa, N. Veerapen, Journal of Heuristics, 2017. The dataset describes the network structure of the local optima networks for Traveling Salesman Problem instances that are sampled using Chained Lin-Kernighan. TSPLIB.zip contains networks from the TSPLIB instances (http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/) that are used in the paper. DIMACSclustered.zip and DIMACSuniform.zip contain networks for instances generated using the DIMACS TSP instance generator (http://dimacs.rutgers.edu/Challenges/TSP/download.html). See README.txt for details on how the networks are represented
Matrix of liana genera surveyed within the Balbina mega-dam system
No full textThis dataset was collected during PhD fieldwork by Isabel Jones. The dataset is a matrix of liana genera found in each site surveyed within the Balbina mega-dam system, Brazilian Amazon.File Matrix_liana_genera_recorded.xlsx records a matrix of liana genera found in each of the sites surveyed within the Balbina mega-dam system, Brazilian Amazon
Bridge and Dementia Study
No full textThe dataset contains a cross section of over 7000 individuals completing a survey exploring the link between the card game Bridge and quality of life. The responses were collected over a three-month period in 2016 through four online questionnaires; these were disseminated via the Bridge community in the UK and further abroad. The survey captures demographic, social, subjective wellbeing, and bridge playing characteristics of individuals.bridge_allsurveys_20160930.dta Stata dataset of over 7000 responses to a 2016 survey exploring the link between playing bridge and individual wellbeing. Data file is from Data Analysis and Statistical Software (STATA) version 13
Woodland creation and Ecological Networks (WrEN)
No full textDataset associated with paper Fuentes-Montemayor E., Watts K., Macgregor N.A., Lopez-Gallego Z. & Park K. (In press) "Species mobility and landscape context determine the importance of local and landscape-level attributes" Ecological Applications. Dataset contains information on local and landscape-level characteristics (reduced into Principal Components obtained from Principal Components Analyses) of 102 woodland patches which form part of the Woodland creation and Ecological Networks project (WrEN; http://wren-project.com/). Bat activity levels (i.e. number of bat passes) recorded at each site are also presented for individual species (P. pygmaeus, P.pipistrellus, P. auritus) or species groups (Myotis sp., Nyctalus sp.).Dataset contains information on local and landscape-level characteristics (reduced into Principal Components obtained from Principal Components Analyses) of 102 woodland patches which form part of the Woodland creation and Ecological Networks project (WrEN; http://wren-project.com/). Bat activity levels (i.e. number of bat passes) recorded at each site are also presented for individual species (P. pygmaeus, P.pipistrellus, P. auritus) or species groups (Myotis sp., Nyctalus sp.)
DAASE: Dynamic Adaptive Automated Software Engineering
No full textReducing computational energy consumption is of growing importance, particularly at the extremes (i.e. mobile devices and datacentres). Despite the ubiquity of the Java Virtual Machine (JVM), very little work has been done to apply Search Based Software Engineering (SBSE) to minimize the energy consumption of programs that run on it.
The paper describes Opacitor, a tool for measuring the energy consumption of JVM programs using a bytecode level model of energy cost. This is combined with generic SBSE approaches to achieve substantial energy savings for three widely-used software components.
Multi-Layer Perceptron implementations minimising both energy and error were found, and energy reductions of up to 70% and 39.85% were obtained over the original code for Quicksort and Object-Oriented container classes respectively.
This data set includes the raw results from the experiments, generated instances for the quicksort experiments, and test code written for Guava's container classes. Dedicated UnZip software is recommended for accessing the dataset, for example, IZArc.File content and descriptions are contained in README.txtSource code for the Opacitor tool is available on request from: Dr Alexander Edward Ian Brownlee (University of Stirling address: [email protected]); the other libraries and data sets used in the work are publicly available at the URLs cited in the paper: OpenJDK http://openjdk.java.net ; Google Guava version 18 https://github.com/google/guava/wiki/Release18 ; Apache Commons Collections version 4.0 commons.apache.org/proper/commons-collections/release_4_0.html ; Apache Commons Math library commons.apache.org/proper/commons-math/userguide/genetics.html ; WEKA http://www.cs.waikato.ac.nz/~ml/weka/ ; Astraiea https://github.com/JerrySwan/Astraie
DAASE: Dynamic Adaptive Automated Software Engineering
No full textThe dataset contains landscape data for "Modelling Genetic Improvement Landscapes with Local Optima Networks", N. Veerapen, F. Daolio, G. Ochoa. In Proceedings of GECCO ’17 Companion, Berlin, Germany, July 15-19, 2017. The dataset contain the execution traces of Iterated Local Search runs on the code of two small programs (Triangle and TCAS) which are incrementally mutated. Dedicated UnZip software is recommended for accessing the dataset, for example, IZArc.The dataset contains landscape data for "Modelling Genetic Improvement Landscapes with Local Optima Networks", N. Veerapen, F. Daolio, G. Ochoa. In Proceedings of GECCO ’17 Companion, Berlin, Germany, July 15-19, 2017. The dataset contain the execution traces of Iterated Local Search runs on the code of two small programs (Triangle and TCAS) which are incrementally mutated. The files are compressed within four zip files. triangle_comparison_ops.zip contains traces of the triangle program where comparison operators are mutated. triangle_comparison_boolean_ops.zip contains traces of the triangle program where comparison and Boolean operators are mutated. tcas_comparison_ops.zip contains traces of the TCAS program where comparison operators are mutated. tcas_comparison_boolean_ops.zip contains traces of the TCAS program where comparison and Boolean operators are mutated
Improving Charity Accountability: Lessons From the Scottish Experience
No full textThis dataset is for the article: McDonnell, D. (2017) Improving Charity Accountability Lessons: From the Scottish Experience. DOI: https://doi.org/10.1177/0899764017692039. The article examines the relevance and effectiveness of a charity accountability monitoring program in Scotland. The Scottish charity sector is vibrant and growing but the regulatory regime is in flux. Drawing upon a novel panel dataset of 21,322 observations on 5,124 organizations for the period 2007-2013, this study examines charity accountability from the perspective of the regulator and analyzes its attempts to encourage acceptable norms and practices in the sector. The results reveal that a majority of these charities trigger accountability concerns and a minority do so persistently; however, this study finds no link between these concerns and negative organizational outcomes such as public complaints, regulatory intervention, or charity dissolution. The article suggests that Scotland’s regulatory body should collaborate with the charity sector to reconsider the program’s intended impact and priorities, and reflects on alternative indicators of accountability. The study utilises administrative panel data derived from the Scottish Charity Regulator (OSCR) for the period 2007-2013. Charities must submit an annual return form and set of financial accounts for each accounting year. The dataset utilised for this research is constructed from two sources: financial exceptions data and annual returns information. The first data source captures instances where a charity’s annual accounts trigger one or more exception codes; the second source contains detailed organizational and financial attributes of charities.improvingcharityaccountability_20170411.dta - File from Data Analysis and Statistical Software (STATA) version 13; improvingcharityaccountability_20170411.csv - Comma Separated Values datase
DAASE: Dynamic Adaptive Automated Software Engineering
No full textThe dataset contains landscape data for "Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study", G. Ochoa, N. Veerapen, F. Daolio, M. Tomassini. The 17th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2017), 19-21 April 2017, Amsterdam, The Netherlands. The dataset describes the network structure of the local optima networks (LON) for Number Partitioning Problem (NPP) instances of size 10, 15 and 20, and with values of parameter k from 0.4 to 1.2 in steps of 0.1. Dedicated UnZip software is recommended for accessing the dataset, for example, IZArc.The dataset contains landscape data for "Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study", G. Ochoa, N. Veerapen, F. Daolio, M. Tomassini. The 17th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2017), 19-21 April 2017, Amsterdam, The Netherlands. The dataset describes the network structure of the local optima networks (LON) for Number Partitioning Problem (NPP) instances of size 10, 15 and 20, and with values of parameter k from 0.4 to 1.2 in steps of 0.1. The files are compressed within npp_phasetransitions_lon.zip and details on how to interpret the contents are given in readme.txt
The determinants of charity misconduct
No full textCharities in the UK have been the subject of intense media, political and public scrutiny in recent times; however our understanding of the nature, extent and determinants of charity misconduct is weak. Drawing upon a novel administrative dataset of 25,611 charities for the period 2006-2014 in Scotland, we develop models to predict two dimensions of charity misconduct: regulatory investigation and subsequent action. There have been 2,109 regulatory investigations of 1,566 Scottish charities over the study period, of which 31 percent resulted in regulatory action being taken. Complaints from members of the public are most likely to trigger an investigation, while the most common concerns relate to general governance and misappropriation of assets. Our multivariate analysis reveals a disconnect between the types of charities that are suspected of misconduct and those that are subject to subsequent regulatory action. This study employs administrative data derived from the Scottish Charity Regulator (OSCR) for the period 2006-2014. It covers the population of Scottish charities over this period and is constructed from three sources: the Scottish Charity Register, which is the official, public record of all charities that have operated in Scotland; annual returns, which are used to populate many of the fields on the Register (e.g. annual gross income); and internal OSCR departmental data relating to misconduct investigations.charityinvestigations_20170411.dta - Stata dataset; charityinvestigations_20170411.csv - Comma Separated Values datase
GABON: maintain long-standing scientific profile
No full textData to accompany manuscript, Bush et al., "Towards effective monitoring of tropical phenology: maximising returns and reducing uncertainty in long-term studies”. Abstract for the publication is: Phenology is a key component of ecosystem function and is increasingly included in assessments of ecological change. We consider how existing, and emerging, tropical phenology monitoring programs can be made most effective by investigating major sources of noise in data collection at a long-term study site. Researchers at Lopé NP, Gabon, have recorded monthly crown observations of leaf, flower and fruit phenology for 88 plant species since 1984. For a subset of these data, we first identified dominant regular phenological cycles, using Fourier analysis, and then tested the impact of observation uncertainty on cycle detectability, using expert knowledge and generalized linear mixed modelling (827 individual plants of 61 species). We show that experienced field observers can provide important information on major sources of noise in data collection and that observation length, phenophase visibility and duration are all positive predictors of cycle detectability. We find that when a phenological event lasts > 4 weeks, an additional 10 years of data increases cycle detectability by 114 percent and that cycle detectability is 92 percent higher for the most visible events compared to the least. We also find that cycle detectability is four times as high for flowers compared to ripe fruits after 10 years. To maximise returns in the short-term, resources for long-term monitoring of phenology should be targeted towards highly visible phenophases and events that last longer than the observation interval. In addition, programs that monitor flowering phenology are likely to accurately detect regular cycles more quickly than those monitoring fruits, thus providing a baseline or future assessments of change.(1.) Fourier_outputs_for_each_individual_tree_phenophase.csv - Spreadsheet of Fourier outputs for each individual tree and phenophase (2.) Fourier_outputs_for_each_individual_tree_phenophase_metadata.csv - Spreadsheet with metadata for 'Fourier_outputs_for_each_individual_tree_phenophase.csv' (3.) Observer_scores_by_species_phenophase.csv - Spreadsheet of observer scores for each species and phenophase (4.) Observer_scores_by_species_phenophase_metdata.csv - Spreadsheet with metadata for 'Observer_scores_by_species_phenophase.csv