Diabetic Retinopathy is the most prevalent cause of avoidable vision impairment, mainly affecting the working-age population in the world. Recent research has given a better understanding of the requirement in clinical eye care practice to identify b...
A key enabler of intelligent maintenance systems is the ability to predict the remaining useful lifetime (RUL) of its components, i.e., prognostics. The development of data-driven prognostics models requires datasets with run-to-failure trajectories....
This work has been carried out to support the investigation of the electroencephalogram (EEG) Fourier power spectral, coherence, and detrended fluctuation characteristics during performance of mental tasks. To this aim, the presented dataset contains...
The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable forestall of vis...
Recently, there has been a growing research interest in utilizing the electroencephalogram (EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article provides a detailed description of a resting-state EEG dataset of individu...
Traumatic brain injuries may cause intracranial hemorrhages (ICH). ICH could lead to disability or death if it is not accurately diagnosed and treated in a time-sensitive procedure. The current clinical protocol to diagnose ICH is examining Computeri...
With advances in Building Information Modeling (BIM), Virtual Reality (VR) and Augmented Reality (AR) technologies have many potential applications in the Architecture, Engineering, and Construction (AEC) industry. However, the AEC industry, relative...
Deep learning, more specifically deep convolutional neural networks, is fast becoming a popular choice for computer vision-based automated pavement distress detection. While pavement image analysis has been extensively researched over the past three...
In this paper, we study the usage of machine-learning models for sales predictive analytics. The main goal of this paper is to consider main approaches and case studies of using machine learning for sales forecasting. The effect of machine-learning g...
Benchmark open-source Wi-Fi fingerprinting datasets for indoor positioning studies are still hard to find in the current literature and existing public repositories. This is unlike other research fields, such as the image processing field, where benc...
Drought indices are essential metrics for quantifying drought severity and identifying possible changes in the frequency and duration of drought hazards. In this study, we developed a new high spatial resolution dataset of drought indices covering al...
The article presents University of Idaho-Physical Rehabilitation Movement Data (UI-PRMD), a publically available data set of movements related to common exercises performed by patients in physical rehabilitation programs. For the data collection, 10...
WiFi fingerprinting, one of the most popular methods employed in indoor positioning, currently faces two major problems: lack of robustness to short and long time signal changes and difficult reproducibility of new methods presented in the relevant l...
Because of the increasing relevance of the Internet of Things and location-based services, researchers are evaluating wireless positioning techniques, such as fingerprinting, on Low Power Wide Area Network (LPWAN) communication. In order to evaluate...
Recently there has been an exponential increase in the use of artificial intelligence for trading in financial markets such as stock and forex. Reinforcement learning has become of particular interest to financial traders ever since the program Alpha...
Twitter is a social media platform where over 500 million people worldwide publish their ideas and discuss diverse topics, including their health conditions and public health events. Twitter has proved to be an important source of health-related info...
Higher education institutions record a significant amount of data about their students, representing a considerable potential to generate information, knowledge, and monitoring. Both school dropout and educational failure in higher education are an o...
The development of mathematical simulation and optimization models and algorithms for solving gas transport problems is an active field of research. In order to test and compare these models and algorithms, gas network instances together with demand...
Developers of resource-allocation and scheduling algorithms share test datasets (i.e., benchmarks) to enable others to compare the performance of newly developed algorithms. However, mostly it is hard to acquire real cloud datasets due to the users&r...
Wearable heart rate sensors such as those found in smartwatches are commonly based upon Photoplethysmography (PPG) which shines a light into the wrist and measures the amount of light reflected back. This method works well for stationary subjects, bu...
It is recognized that the performance of any prediction model is a function of several factors. One of the most significant factors is the adopted preprocessing techniques. In other words, preprocessing is an essential process to generate an effectiv...
In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use Artificial Intelligence (AI) and ML to assess credit risk, analyzing large volumes of informati...
The present paper concerns the design of the semantic infrastructure of the data space for cultural heritage as envisaged by the European Commission in its recent documents. Due to the complexity of the cultural heritage data and of their intrinsic i...
With the extensive growth of user interactions through prominent advances of the Web, sentiment analysis has obtained more focus from an academic and a commercial point of view. Recently, sentiment analysis in the Bangla language is progressively bei...
We estimate treatment cost-savings from early cancer diagnosis. For breast, lung, prostate and colorectal cancers and melanoma, which account for more than 50% of new incidences projected in 2017, we combine published cancer treatment cost estimates...
The natural and semi-natural areas within cities provide important refuges for biodiversity, as well as many benefits to people. To study urban ecology and quantify the benefits of urban ecosystems, we need to understand the spatial extent and config...
The digital twin has recently become a popular topic in research related to manufacturing, such as Industry 4.0, the industrial internet of things, and cyber-physical systems. In addition, digital twins are the focus of several research areas: constr...
One crucial parameter to evaluate the state of the heart after myocardial infarction (MI) is the viability of the myocardial segment, i.e., if the segment recovers its functionality upon revascularization. MRI performed several minutes after the inje...
(1) Background: The importance of this article is to analyze the technological developments in the field of the Internet and Internet technologies and to determine their significance for sustainable development, which will result in the emergence of...
The Himalaya is the largest mountain range in the world, spanning approximately ten degrees of latitude and elevation between 100 m asl to the highest mountain peak on earth. The region varies in plant species richness, being highest in the biodivers...
Automatic and interactive data analysis is instrumental in making use of increasing amounts of complex data. Owing to novel sensor modalities, analysis of data generated in professional team sport leagues such as soccer, baseball, and basketball has...
This study aims at assessing the feasibility of automatically producing analysis-ready radiometrically terrain-corrected (RTC) Synthetic Aperture Radar (SAR) gamma nought backscatter data for ingestion into a data cube for use in a large spatio-tempo...
Liver cancer is the sixth most common cancer in the world and the fourth leading cause of cancer mortality. In unresectable liver cancers, especially hepatocellular carcinoma (HCC), transarterial radioembolisation (TARE) can be considered for treatme...
Hydrologic soil groups play an important role in the determination of surface runoff, which, in turn, is crucial for soil and water conservation efforts. Traditionally, placement of soil into appropriate hydrologic groups is based on the judgement of...
Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance...
Datasets are important for researchers to build models and test how well their machine learning algorithms perform. This paper presents the Rainforest Automation Energy (RAE) dataset to help smart grid researchers test their algorithms that make use...
Many clinical research datasets have a large percentage of missing values that directly impacts their usefulness in yielding high accuracy classifiers when used for training in supervised machine learning. While missing value imputation methods have...
This paper intends to present a new model for the accurate forecast of the stock’s future price. Stock price forecasting is one of the most complicated issues in view of the high fluctuation of the stock exchange and also it is a key issue for...
Earth observation data cubes are increasingly used as a data structure to make large collections of satellite images easily accessible to scientists. They hide complexities in the data such that data users can concentrate on the analysis rather than...
The paper describes a new non-iterative linear supervised learning predictor. It is based on the use of Ito decomposition and the neural-like structure of the successive geometric transformations model (SGTM). Ito decomposition (Kolmogorov–Gabor poly...
The past decade has witnessed the rapid development of machine learning applied in economics and finance. Recent evidence suggests that machine learning models have produced superior results to traditional statistical models and have become the drivi...
Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) trans...
In recent years, education institutions have offered a wide range of course selections with overlaps. This presents significant challenges to students in selecting successful courses that match their current knowledge and personal goals. Although man...
Accurate and timely information on the global cropland extent is critical for food security monitoring, water management and earth system modeling. Principally, it allows for analyzing satellite image time-series to assess the crop conditions and per...
Earth Observation Data Cubes (EODC) have emerged as a promising solution to efficiently and effectively handle Big Earth Observation (EO) Data generated by satellites and made freely and openly available from different data repositories. The aim of t...
Some of the recent developments in data science for worldwide disease control have involved research of large-scale feasibility and usefulness of digital contact tracing, user location tracking, and proximity detection on users’ mobile devices...
Irreversible vision loss is a worldwide threat. Developing a computer-aided diagnosis system to detect retinal fundus diseases is extremely useful and serviceable to ophthalmologists. Early detection, diagnosis, and correct treatment could save the e...
The spatial distribution of humans on the earth is critical knowledge that informs many disciplines and is available in a spatially explicit manner through gridded population techniques. While many approaches exist to produce specialized gridded popu...
In this article, we present a dataset that comprises different physical rehabilitation movements. The dataset was captured as part of a research project intended to provide automatic feedback on the execution of rehabilitation exercises, even in the...
The emerging global trend of satellite operators producing analysis-ready data combined with open source tools for managing and exploiting these data are leading to more and more countries using Earth observation data to drive progress against key na...
