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Microsoft contains a productive tool known as MS Office but the inclusion of VBA Macros inside the MS Office for automation purposes makes it a way for attackers to perform malicious activities. To get an up-to-date dataset, the research regarding VBA macros is still working to find efficient ways to detect it. To perform analysis, the dataset is required which is publically harder to find. To overcome this issue, a dataset is created from VirusTotal, VirusShare, Zenodo, Malware Bazaar, Github and InQuest Labs.
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The dataset contains detailed information on a 100kVA transformer in ONAN cooling mode. The file consists of three PDF documents, which describe the transformer’s overall structure, core structure and size, winding structure and dimension, respectively.
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The dataset contains development archives of more or less interesting conversations, announcements, discussions, presentations and so on regarding consensus changes in Bitcoin.
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The datasets consist of operational data and detailed information of three inverter transformers in a 3.275 MW PV plant in the outskirt of Brisbane, Australia. The data includes load current, top-oil temperature, moisture in top oil, ambient temperature, solar irradiance and individual current harmonics (up to 31st order). The time interval of the data is either 1 minute or 3 seconds (dependent on the data type). The data can be used to study the ageing of inverter transformers in this PV plant.
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The integrated power grid in USA is the largest in the world with the highest hourly power demand. In 2019, the highest hourly demand was more than 704 GW and the lowest hourly demand was less than 340 GW. The average daily variation in hourly demand is about 40% with respect to the highest hourly demand. A mathematical model is used to reduce the differential between peak and off-peak electrical power demand in this territory. The reduction is achieved with 5 time zones set up across US 48 states such that time difference between Far East and Far west is 4 hours.
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In this paper presented method for reducing the amount of data transmitted and stored in IoT systems. Instead of expensive and complex network devices, developers can apply cheap and proven low-speed solutions (ZigBee, NB IoT, BLE). This approach is focused on on-the-sensor data processing. Correlation and autocorrelation methods for detecting events, depending on shape of a wave, were described in details and proposed endpoint architecture implementation.
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The dataset comprises raw data to validate methods for reliable data collection. We proposed the data collection methods in a path to assess digital healthcare apps. To validate the methods, we conducted experiments in Amazon Mechanical Turk (MTurk), and then we showed that the methods have a significant meaning based on statistical tests.
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Appendix for Principal Components
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