Machine Learning

This comprehensive dataset comprises multiple files, encompassing essential information on various aspects of power systems. It includes the active and reactive power consumption data for both the 33- and 136-bus test systems, along with the resistance and reactance values of the distribution lines, and the network structure.

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Set of samples resulting from an evaluative, population-based cross-sectional study, approved by the Research Ethics Committee of Federal University of Alfenas, protocol: 415856. These samples pertain to 1,027 rural workers from the southern region of Minas Gerais, Brazil, where comprehensive data on socioeconomic factors, history of pesticide intoxication and hospitalization, and usage of personal protective equipment were collected. Blood samples were obtained to measure biomarkers of pesticide exposure as well as indicators of renal and hepatic sequelae.

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732 Views

Seven years of water consumption data, along with population data, were manually collected in collaboration with the local municipality office. This data was then combined with climatic data to model the proposed machine learning algorithm. The weather data was recorded for a period of 7 years using precise meteorological instruments installed in Islamabad at coordinates 33.64° N and 72.98° E, with an elevation of 500 meters above sea level.

 

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737 Views

We present the RQMD dataset, a comprehensive collection of diverse material samples aimed at advancing computer vision and machine learning algorithms in terrain classification tasks. This dataset contains RGB images of 5 different terrains, such as Asphalt, Brick, Grass, Gravel, and Tiles, captured using an 8-megapixel Raspberry Pi camera from a top-view perspective. Notably, the dataset encompasses images taken at different times of the day, introducing variations in lighting conditions and environmental factors.

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448 Views

The significance of having sustainable water quality data cannot be overstated. It plays a crucial role in comprehending the historical variations and patterns in river conditions and also helps in understanding how industrial waste impacts the well-being of aquatic ecosystems. To achieve sustainable water management practices, it is imperative to rely on dependable and extensive data. Therefore, accurate monitoring and assessment of various water quality parameters become essential.

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1062 Views

In agriculture, the development of early treatment techniques for plant leaf diseases can be significantly enhanced by employing precise and rapid automatic detection methods. Within this realm of research, two common scenarios encountered in real field cases are the identification of different severity stages of diseases and the detection of multiple pathogens simultaneously affecting a single plant leaf. One major challenge faced in this area is the lack of publicly available datasets that contain images captured under these specific conditions.

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200 Views

We created a 5G dataset by measuring 5G traffic directly from a major mobile operator in South Korea. The model name of the mobile terminal used for traffic measurement is the Samsung Galaxy A90 5G, equipped with a Qualcomm Snapdragon X50 5G modem. We installed PCAPdroid, a packet sniffer software, on the terminal via Google Play. Traffic was measured sequentially per application on two stationary terminals (only one terminal is used for noninteractive services) with no background traffic.

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5979 Views

Lantana flower, originally known as a parasitic and poisonous plant, is expansive to fill many livestock fields. Lantana data sets are open source and can be used by many researchers to create models with higher accuracy. currently the accuracy using this dataset has reached 99.8% using k-NN and preceded by feature extraction using VGG-16 Lantana flower, originally known as a parasitic and poisonous plant, is expansive to fill many livestock fields. Lantana data sets are open source and can be used by many researchers to create models with higher accuracy.

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193 Views

This dataset is a subset from the Oxford University Our World in Data Covid 19 Dataset. This dataset contains data points collected on an ongoing basis from Johns Hopkins University, Center for Systems Science and Engineering COVID-19 data, OXFORD COVID-19 Government Response Tracker, and European Centre for Disease Control, from January 2020 to present.

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162 Views

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