*.csv (zip)
We build an original dataset of thermal videos and images that simulate illegal movements around the border and in protected areas and are designed for training machines and deep learning models. The videos are recorded in areas around the forest, at night, in different weather conditions – in the clear weather, in the rain, and in the fog, and with people in different body positions (upright, hunched) and movement speeds (regu- lar walking, running) at different ranges from the camera.
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Coventry-2018 is a human activity recognition dataset captured by three Panasonic® Grid-EYE (AMG8833) infrared sensors in March 2018. The Grid-EYE sensors represent a 60 field of view scene by an 8 × 8 array named frame. The data streams are synchronized to 10 frames per second and saved as *.csv recordings using the LabVIEW® software. Two layouts are considered in this dataset with different geometry sizes: 1) small layout; and 2) large layout.
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Presented here is a dataset used for our SCADA cybersecurity research. The dataset was built using our SCADA system testbed described in our paper below [*]. The purpose of our testbed was to emulate real-world industrial systems closely. It allowed us to carry out realistic cyber-attacks.
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Message Queuing Telemetry Transport (MQTT) protocol is one of the most used standards used in Internet of Things (IoT) machine to machine communication. The increase in the number of available IoT devices and used protocols reinforce the need for new and robust Intrusion Detection Systems (IDS). However, building IoT IDS requires the availability of datasets to process, train and evaluate these models. The dataset presented in this paper is the first to simulate an MQTT-based network. The dataset is generated using a simulated MQTT network architecture.
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This dataset mainly consists 1) source codes of wide-attention and deep model (WADC); 2) datasets to evaluate the performance of the proposed model. Datasets are obtained from the Caltrans Performance Measurement System (CPeMS) http://pems.doc.ca.gov; and Fremont Bridge Bicycle Counter (FBBC), https://data.seattle.gov.
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Database set information
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Dataset used for "A Machine Learning Approach for Wi-Fi RTT Ranging" paper (ION ITM 2019). The dataset includes almost 30,000 Wi-Fi RTT (FTM) raw channel measurements from real-life client and access points, from an office environment. This data can be used for Time of Arrival (ToA), ranging, positioning, navigation and other types of research in Wi-Fi indoor location. The zip file includes a README file, a CSV file with the dataset and several Matlab functions to help the user plot the data and demonstrate how to estimate the range.
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Power transmission system losses can typically represent from five to ten percent of the total generation, a quantity worth millions of dollars per year. The purpose of loss allocation in the context of pool dispatch is to assign to each individual generation and load the responsibility of paying for part of the system transmission losses. Since the system losses are non-separable, non-linear functions of the real power generation and loads, the allocation of transmission loss is a challenging and contentious issue in a fully deregulated system.
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This is the dataset used in our journal paper, submitted to: IEEE Transactions on Dependable and Secure Computing, Special Issue on Explainable Artificial Intelligence for Cyber Threat Intelligence (XAI-CTI) Applications.
Submitted = 12-Jan-2021 (under review)
ID = TDSCSI-2021-01-0045
Source codes are available at IEEE Code Ocean:
Hatma Suryotrisongko (2020) Botnet DGA [Source Code]. https://doi.org/10.24433/CO.4005597.v2
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The aircraft fuel distribution system has two primary functions: storing fuel and distributing fuel to the engines. These functions are provided in refuelling and consumption phases, respectively. During refuelling, the fuel is first loaded in the Central Reservation Tank and then distributed to the Front and Rear Tanks. In the consumption phase, the two engines receive an adequate level of fuel from the appropriate tanks. For instance, the Port Engine (PE) will receive fuel from Front Tank and the Starboard Engine (SE) will receive fuel from Rear Tank.
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