University of La Laguna Showcase

Knapsack Problem instances for N = 50 generated with various Quality Diversity Methods. Each instance includes its target solver and the method used to generate it.

Travelling Salesman Problem instances for N = 50 generated with various Quality Diversity Methods. Each instance includes its target solver and the method used to generate it.

Bin Packing problem instances for N = 120. The dataset includes the target solver and the generation method employed to produce such instance.

Base de datos resultante de los cuestionarios realizados durante los talleres de ODS. Se encuentran agrupados los cuestionarios ex ante y ex post

Experimental and simulated light-off curves

Article data Characterisation of fear of public speaking and social cognition. A machine learning study.

The study goal was to identify the cultural model that stakeholder groups use to determine whether their cultural views of property rights (use and access) and management techniques differed among the surveyed island regions: El Hierro (Canary Islands, Spain); Mahé, Praslin and La Diegue Islands (Seychelles) and Dunde (Solomon Islands). The dataset contains results from an agreement questionnaire based on the Cultural Consensus Analysis (Bernard, 2000). Within every community (zone) on each island region, a random stratified sample of households was chosen. Each interview was conducted with a chosen household head in the local language. Interviewers were also indigenous from each region and had previous experience working on every zone, employing qualitative research tools. A total of 400 surveys were conducted at the sampled locations within the island groups. The research methods and activities were approved by Rhodes University Human Research Ethics Committee (RU-HREC), approval number 2023-5096-8105. Ecosdyn (Eco-social Dynamics Consulting) and the University of La Laguna were also involved in the study and dataset development.

New benchmark instances for the Cross-Dock Door Assignment and Scheduling Problem (CDSP) and capacities at the inbound/outbound doors, with instances from eight origins and destinations, four inbound and outbound doors, up to 50 origins and destinations, and 30 inbound and outbound doors. The instances have been obtained following the criteria of the paper by Nassief et al. (2016), with some modifications. First, the number of pallets to be moved from a supplier to a customer is randomly generated using a uniform distribution U[1,5] until density values are set to 25, 35, 50, and 75%. Each inbound truck sends pallets from at least one outgoing truck, and each outgoing truck receives pallets from at least one incoming truck. The distance matrix is generated with numbers from the interval [1, 1 + |I|- 1], meaning that a direct distance between two doors equals 1, and then an increment of 1 unit is added for the next indirect door. The number of considered incoming/outgoing trucks is 8, 9, 10, 11, 12, 15, 20, and 50. The number of considered inbound/outbound doors is 4, 5, 6, 7, 10, and 30. The door capacities are equal for each instance and calculated by dividing the total flow from all origins by the total number of inbound doors and then adding a capacity slackness of 5, 10, 15, 20, and 30%. To generate this set of instances, we have considered the combinations of values reported in the paper by Sayed (2020). The instances are referred to as 00×00×00x00 (number of the incoming and outgoing trucks x number of inbound and outbound doors x capacity slackness associated with the inbound/outbound doors - 5, 10, 15, 20, and 30% - x density of the flow matrix - 25, 35, 50, and 75%).

EEG brain state-dependent design that leverages real-time variations in alpha power to modulate the loudness (volume) of pre-recorded audio files during an experimental task akin to the traditional Digit Span test. The study assesses whether the perceptual intensity of speech signals can modulate speech tracking and short-term memory.

This dataset referred contains 15,000 synthetic signatory records, each corresponding to a different simulated individual. Each record includes an ID (a unique personal identifier following the Spanish Home Office format, consisting of eight numeric digits followed by a single alphabetic character) and a signature associated with that individual. The dataset is used to evaluate the performance of a transformer-based OCR system for handwritten signature verification for lawmaking petitions submitted by citizens.