Machine Learning
As the Internet of Things (IoT) continues to evolve, securing IoT networks and devices remains a continuing challenge.The deployment of IoT applications makes protection more challenging with the increased attack surfaces as well as the vulnerable and resource-constrained devices. Anomaly detection is a crucial procedure in protecting IoT. A promising way to perform anomaly detection on IoT is through the use of machine learning algorithms. There is a lack in the literature to identify the optimal (with regard to both effectiveness and efficiency) anomaly detection models for IoT.
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272 Views
This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relavant information about the patient.
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4876 Views
STP dataset is a dataset for Arabic text detection on traffic panels in the wild. It was collected from Tunisia in “Sfax” city, the second largest Tunisian city after the capital. A total of 506 images were gathered through manual collection one by one, with each image energizing Arabic text detection challenges in natural scene images according to real existing complexity of 15 different routes in addition to ring roads, roundabouts, intersections, airport and highways.
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228 Views
Climate change has been a worldwide concern for more than 50 years now and climate change misinformation has also been a critical issue as it questions the causes and effects of climate change, hence disturbing climate action. Climate misinformation has been a major obstacle to mitigating climate change and its effects, and it even aggravated the issue and polarized the public. In this paper, we introduce a new climate change misinformation and stance detection dataset namely ClimateMiSt, consisting of both social media data and news article data with manually verified labels.
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810 Views
The dataset, developed at the National Institute of Neurology and Neurosurgery in Mexico, encapsulates crucial gait biomarkers associated with neurodegenerative diseases. This invaluable compilation serves as a comprehensive resource for understanding and analyzing the distinctive gait patterns exhibited by patients grappling with neurological disorders. By delving into these intricate biomarkers, researchers gain insights into the nuanced manifestations of conditions impacting the nervous system.
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192 Views
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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2949 Views
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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260 Views
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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185 Views
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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3155 Views
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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1416 Views