Machine Learning
We obtained this dataset as part of a project to generate a realistic speed profile on a trip specified by GPS coordinates. Specifically, we focused on generating the speed profile for a passenger car traveling on an unfamiliar route, i.e., a route the machine-learning model has yet to see.
The dataset contains 5973 rides of five different passenger cars, with a total length of 9049.3 km. The data was collected during 2021 in the Czech Republic and includes municipal and non-municipal trips.
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Compared with traditional finance, digital finance introduces digital technology for financial innovation, which largely reduces financial exclusion and discrimination, but improved financial services, such as mobile payment, online lending, virtual currency, and investment and wealth management, also involve potential risks. Hence, we propose a sentiment analysis model, GABP-News, to study the predictive ability of the information contained in news texts on digital financial development in China.
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Please cite the following paper when using this dataset:
N. Thakur, S. Cui, K. A. Patel, N. Azizi, V. Knieling, C. Han, A. Poon, and R. Shah, “Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis and Forecasting of Web Behavior,” Journal of Computation, Vol. 11, Issue. 11, Article. 234, Nov. 2023, DOI: http://dx.doi.org/10.3390/computation11110234
Abstract
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The Integrated Energy Management and Forecasting Dataset is a comprehensive data collection specifically designed for advanced algorithmic modeling in energy management. It combines two distinct yet complementary datasets - the Energy Forecasting Data and the Energy Grid Status Data - each tailored for different but related purposes in the energy sector.
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The rapid evolution of communication networks and the ever-increasing demand for efficient data transfer have led to the development of cognitive networking, which aims to enhance network performance through intelligent and adaptive protocols. To facilitate research and development in this domain, we present a comprehensive dataset detailing the parameters of a Network Protocol Stack which can be used to develop a Cognitive Network Protocol Stack designed for efficient networking.
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The poor posture is one of the main common health problems in the growth of adolescents, which seriously affects their physical and mental health. The posture gait recognition is a premise for preventing and correcting the poor posture. This paper proposes a gait recognition method for poor posture based on PCA-BP neural network. Using wearable intelligent insoles to measure plantar pressure, a gait recognition model based on PCA-BP neural network model is constructed.
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The VNA dataset has three features: frequency, S21, and phase, while the MIMO dataset has an additional 'Channel' feature. The VNA dataset is larger than the MIMO dataset, with 507,709 rows compared to 164,161 rows in the MIMO dataset. This is because the VNA dataset was sampled at a 1 MHz resolution, while the MIMO dataset was sampled at a 25 MHz resolution, which is the limit set by the MATLAB API. As a result, the VNA dataset provides 4,701 samples per tag, while the MIMO dataset provides 190 samples per tag per channel for each reading.
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As the harmful effects of climate change on human society increase, the analysis of abnormal weather is becoming an important issue. Therefore, this work provides the Korean weather dataset, including the anomaly score measurements by using seven different methods. In this dataset, seven types of weather data for each day in 64 Korean cities from 2010 to 2020 are provided by Weather Radar Center in Korea Meteorological Administration.
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As the harmful effects of climate change on human society increase, the analysis of abnormal weather is becoming an important issue. Therefore, this work provides the Korean weather dataset, including the anomaly score measurements by using seven different methods. In this dataset, seven types of weather data for each day in 64 Korean cities from 2010 to 2020 are provided by Weather Radar Center in Korea Meteorological Administration.
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Low-light images and video footage often exhibit issues due to the interplay of various parameters such as aperture, shutter speed, and ISO settings. These interactions can lead to distortions, especially in extreme lighting conditions. This distortion is primarily caused by the inverse relationship between decreasing light intensity and increasing photon noise, which gets amplified with higher sensor gain. Additionally, secondary characteristics like white balance and color effects can also be adversely affected and may require post-processing correction.
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