*.avi; *.csv; *.txt

Latent fingerprint identification is crucial in forensic science for linking suspects to crime scenes. Latent examiners obtain unique, reliable evidence by revealing hidden prints through advanced techniques. However, latent fingerprints often are partial prints with undesirable characteristics such as noise or distortion. Due to these characteristics, identifying the physical details of a latent fingerprint, known as minutiae, is a complex task. Recent publications found that there are subsets on one minutia in latent fingerprints that, when removed, increase the matching score.
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Dataset from UCI contains the electricity consumption (in kWh) of 320 customers every 15 minutes from 2011 to 2014. For some customers, their electricity consumption data was recorded starting from a different time, and the data before the first record was marked as 0. As training model requires a starting point for the time series, and different customers have different starting times, some features remain 0 before a certain time point. Using all the data for training would inevitably have a negative impact. Therefore, the data from 2011 is removed and set the starti
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We use a total of 16 datasets, detailed descriptions of which are provided in Table II. Among them, 11 datasets are from the UCI database, the DLBCL-Harvard dataset is from the ELVIRA biomedical database, Yale and ORL
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This dataset was used for the capacity planing of ahybrid solar PV-small hydro power plant located in Buseruka, Hoima District in Uganda. The data consitss of four files namely:
1. 20240601_GenerationStatisticsQ1_2024-Kabalega-Hydromax: Represents power generation statistics from ERA for Kabalega/HYdromax HPP.
2. Hydrology from Buseruka HPP - 2015-2022: Represents the hydrology or river flow data in cumecs for the period 2015 to 2022 as provided by the plant operators.
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These datasets are collected from the tests that were performed for decentralized synchronization among collaborative robots via 5G and Ethernet networks using with/without causal message ordering. These files have different names depending on the connection type and causality type. For example, 5G_with_causality.txt file stores the test results which were performed on a public 5G network using causal message ordering for different cobot groups like 5,10,20,30,40. The test results for each robot group are separated in each txt file.
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This corpus comprises a diverse collection of authentic dialogues extracted from clinical encounters and from AI-generated interactions. Encompassing a wide array of scenarios, it offers a comprehensive snapshot of human communication within medical contexts and the evolving capabilities of AI. By intertwining genuine exchanges with those produced by AI models, the corpus facilitates a deeper understanding of communication dynamics and the progression of AI technology in simulating human interactions.
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Autistic people typically need methodical support as they explore and interact with their immediate surroundings and the objects associated with them, emphasising the importance of spatial knowledge and cognitive skills in improving and understanding their surroundings. The objective of this research paper is to present a conceptual and technical framework that could be of significant assistance in developing spatial ability and cognitive skills in autistic people.
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We investigated the effect of CW radiation at 0.6 THz on pathological protein aggregates in the form of amyloid fibrils, i.e. ordered protein complexes linked to neurodegenerative diseases such as Parkinson's and Frontotemporal Dementia. To monitor the effect of THz irradiation we exploited mid-infrared (mid-IR) vibrational spectroscopy in the amide-I band range, whose lineshape is known to depend on the protein conformation and on how proteins arrange into ordered supramolecular complexes such as fibrils.
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This study analyzes the spending of Brazilian municipalities on health using an approach based on computational intelligence. The study was characterized by a quantitative and documentary database, and 117 municipalities with an average population between 2004 and 2019 of more than 100,000 inhabitants were analyzed. The data was obtained from the Brazilian Finance database (Finbra) (National Treasury Secretariat) and processed and adjusted for inflation. The main technique used was cluster analysis via R software, version 3.3.3.
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