*.avi; *.csv; *.txt; *.zip

The dataset includes active power measurements for a residential prosumer located in Mogosoaia, Romania, collected at 1 frame/second reporting rate over 12 consecutive months.
Always-on appliances include the refrigerator and the wireless router. Several other appliances are installed in the residential unit: washing machine, lighting fixtures, electrical iron, vacuum cleaner, various ICT charging devices, and air conditioning (seldom used).
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The Defect Tracking dataset provides a comprehensive resource for software maintenance and defect prediction research. This dataset, downloaded from the Jira Spring website, includes detailed defect data from a variety of Spring application projects such as Spring Framework, Spring Boot, Spring Security, Spring Data, and others. It encompasses numerous attributes, including issue summaries, types, statuses, priorities, resolution details, and additional relevant information.
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This study utilizes the annual loan ledger data obtained from a commercial bank located in Jiangsu Province, China, which is called ChinaZJB. The ChinaZJB dataset consists of 1,329 valid samples of SMEs after merging the non-financial behavioral information and soft information on credit rating with the financial information, loan information, and non-financial basic information found in the annual loan ledger data.
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Hydraulic servomotor is a common energy saving hydraulic power component, capable of switching between pump and motor operating conditions. Precise displacement control of hydraulic servomotors is crucial for minimizing throttling losses and improving overall efficiency. However, the accuracy of hydraulic servomotor displacement control is adversely affected by high-frequency uncertainty disturbances in swashplate moment, traditional adaptive robust control did not account for this factor, leading to suboptimal displacement control effectiveness.
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The compressed files to be uploaded include three types: tif, csv, and py files.The compressed files to be uploaded include three types: tif, csv, and py files. These documents are directly related to our article.The following is a brief overview of the following files:
tif: 4160 training set images and 40 test set images.
csv: The AGB value corresponding to each image.
py:The code of data augmentation.
We hope that the documents we uploaded can make some contribution to the research of AGB estimation
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This large dataset includes six small datasets, including two types, one contains the original node relationship information and node feature information, please use it through the common network construction methods; the other is the dataset which has been processed, including the direct edge information and node's association information, which can be used to construct the network directly through the network construction methods.
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This letter presents a new formulation for the lossconcerned dc power flow that is suitable for optimization-based power system operation and planning. The proposed approach equivalently recasts a previously reported model considering non-uniform line flows. More specifically, motivated by industry standards, resistive losses of transmission lines are represented without relying on nodal voltage phase angles, unlike the original model. The proposed angle-free formulation is mathematically equivalent to the angle-based counterpart, i.e., identical line flows and losses are attained.
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This large dataset includes six small datasets, including two types, one contains the original node relationship information and node feature information, please use it through the common network construction methods; the other is the dataset which has been processed, including the direct edge information and node's association information, which can be used to construct the network directly through the network construction methods.
Translated with www.DeepL.com/Translator (free version)
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This dataset includes a subset of the InSDN Dataset to examine the effects of various flow-to-image conversion techniques on the performance of intrusion detection systems (IDS). The dataset contains five types of attacks: Denial of Service (DoS), Distributed Denial of Service (DDoS), Probe, Normal, and Brute Force Attack (BFA). Each instance represents a network flow, which is converted into an image using: Method 1: applies the Image Generator for Tabular Data (IGTD) framework using Euclidean distance, transforming tabular data into grayscale images.
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