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The historical dataset of the meteorological variables was recorded by the Mexican National Water Council (Comisión Nacional del Agua, CONAGUA) ground station located at the city of Mérida, Yucatán, Mexico; the following variables were found: temperature (T), vapor pressure (P), and relative humidity (H). The range dates of the records were from January 1, 2000 to September 30, 2018, where there is a daily record of temperatures with minimum, maximum, and average units, resulting in nine readings provided for each day.
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There is a growing trend towards combining mathematics and computer science education. Although there are surely synergies between the two disciplines, has sufficient thought been given to the benefit of fostering independently the unique skillsets they offer in order to best harness these synergies?
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The increasing complexity of intelligent systems in the Internet of Things (IoT) domain makes it essential to explain their behavior and decision-making processes to users. However, selecting an appropriate explanation method for a particular intelligent system in this domain can be challenging, given the diverse range of available XAI (eXplainable Artificial Intelligence) methods and the heterogeneity of IoT applications. This dataset is a case base elicited from an exhaustive literature review on existing explanation solutions of AIoT (Artificial Intelligence of the Things) systems.
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Smart home automation is part of the Internet of Things that enables house remote control via the use of smart devices, sensors, and actuators. Despite its convenience, vulnerabilities in smart home devices provide attackers with an opportunity to break into the smart home infrastructure without permission. In fact, millions of Z-Wave smart home legacy devices are vulnerable to wireless injection attacks due to the lack of encryption support and the lack of firmware updates.
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The data presented here was acquired using a testbed for biocompatible molecular communication based on magnetic nanoparticles. The folders correspond to the variety of channel parameters that were investigated and two additional data transmission samples. Details regarding the testbed setup can be found in the accompanying publication.
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The India Weather Forecast built a state-level standard rainfall forecast system using a multi-model ensemble approach with model outputs from five prominent worldwide NWP centers. Pre-assigned grid point weights based on anomalous correlations (CC) between values observed and predicted are established for each element model using two seasonal datasets, and multi provision of appropriate predictions are created in real-time similar resolution. Then, forecasts are created for each state node lying within a given district by averaging the ensemble prediction fields' values.
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The data is collected in the form of csv file containing three attributes of X, Y, Z which represents the three coordinates of the graph x, y and z. The csv file is collected from the three signals generated by using a mobile app G sensor logger available publicly from google playstore. The data is generated for the first five Telugu language characters. The data is stored in the form of five folders where each folder represents the respective Telugu character. This dataset can be used for evaluating machine learning algorithms.
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