In recent years, the governments in many countries have recognized the importance of data in boosting their economies. As a result, they are implementing the philosophy of open government data (OGD) to make public data easily and freely available to...
The so-called ‘Industrie 4.0’ provides high potential for data-driven methods in automated production systems. However, sensor and actuator data gathered during normal operation of the system is often limited to a narrow range of single, specific ope...
OpenStreetMap (OSM) is a free map that can be created, edited, and updated by volunteers globally. The quality of OSM datasets is therefore of great concern. Extensive studies have focused on assessing the completeness (a quality measure) of OSM data...
Accurate source locating and a complete data catalogue of the seismic network are the prerequisites for seismic analysis methods to identify coal burst risks. Comprehensively understanding the spatial characteristics of source location errors and sei...
Background: Quality assurance in data collection is essential as data quality directly impacts the accuracy and reliability of outcomes. In the context of early detection of prostate cancer, improving data completeness is a key focus for enhancing pa...
In situ sea surface temperatures (SST) are the key component of the calibration and validation (Cal/Val) of satellite SST retrievals and data assimilation (DA). The NOAA in situ SST Quality Monitor (iQuam) aims to collect, from various sources, all a...
Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in cur...
The purpose of this article is to illustrate an investigation of methods that can be effectively used to predict the data incompleteness of a dataset. Here, the investigators have conceptualized data incompleteness as a random variable, with the over...
Completing traffic data is a basic requirement for intelligent transportation systems. However, completing spatiotemporal traffic data poses a significant challenge, especially for high-dimensional data with complex missing mechanisms. Various comple...
Weather radars commonly suffer from the data-missing problem that limits their data quality and applications. Traditional methods for the completion of weather radar missing data, which are based on radar physics and statistics, have shown defects in...
Real-time process data are the foundation for the successful implementation of intelligent manufacturing in the chemical industry. However, in the actual production process, process data may randomly be missing due to various reasons, thus affecting...
The evolving economic and technological landscape has brought about significant changes in travel behaviors and traffic patterns. These changes have led to the emergence of complex, multi-modal travel demands that interact with transportation network...
This work contributes to the techniques used for SCADA (Supervisory Control and Data Acquisition) system data completion in databases containing historical water sensor signals from a water supplier company. Our approach addresses the data restoratio...
Availability of reliable and extended datasets of recorded power output from renewables is nowadays seen as one of the key drivers to improve the design and control of smart energy systems. In particular, these datasets are needed to train artificial...
Supervisory Control And Data Acquisition (SCADA) systems currently monitor and collect a huge among of data from all kind of processes. Ideally, they must run without interruption, but in practice, some data may be lost due to a sensor failure or a c...
This paper presents a proposal for an Artificial Neural Network (ANN)-based architecture for completion and prediction of data retrieved by underwater sensors. Due to the specific conditions under which these sensors operate, it is not uncommon for t...
The idea behind the Infrastructure for Spatial Information in Europe (INSPIRE) project was to provide EU citizens with access to various types of information, including environmental protection and spatial management data. These resources can be view...
A concrete dam is an important water-retaining hydraulic structure that stops or restricts the flow of water or underground streams. It can be regarded as a constantly changing complex system. The deformation of a concrete dam can reflect its operati...
This retrospective cohort analysis leveraged vaccination data for BNT162b2, mRNA-1273, and Ad26.COV2.S in the United States from the Komodo Healthcare Map database, the TriNetX Dataworks USA Network, and Cerner Real-World EHR (electronic health recor...
Today’s data centers host a variety of different applications that impose specific requirements for their flows. Applications that generate short flows are usually latency sensitive; they require their flows to be completed as fast as possible....
Many models assumed to be able to predict the response of structural systems fail to efficiently accomplish that purpose because of two main reasons. First, some structures in operation undergo localized damage that degrades their mechanical performa...
To obtain efficient data gathering methods for wireless sensor networks (WSNs), a novel graph based transform regularized (GBTR) matrix completion algorithm is proposed. The graph based transform sparsity of the sensed data is explored, which is also...
In this paper, we are interested in the data gathering for Wireless Sensor Networks (WSNs). In this context, we assume that only some nodes are active in the network, and that these nodes are not transmitting all the time. On the other side, the inac...
Sparse sensing schemes based on matrix completion for data collection have been proposed to reduce the power consumption of data-sensing and transmission in wireless sensor networks (WSNs). While extensive efforts have been made to improve the recove...
The leaf area index (LAI) is an important parameter for vegetation monitoring and land surface ecosystem research. Although a variety of LAI products have been generated, the moderate to coarse spatial resolution and low temporal resolution of these...
This paper conducts a rigorous analysis for the problem of robust tensor completion, which aims at recovering an unknown three-way tensor from incomplete observations corrupted by gross sparse outliers and small dense noises simultaneously due to var...
Collecting and analyzing log data can provide students with individualized learning to maintain their motivation and engagement in learning activities and reduce dropout in Massive Open Online Courses (MOOCs). As online learning becomes more and more...
A method is developed that removes a priori information from remotely sensed atmospheric state profiles. This consists of a Wiener deconvolution, whereby the required cost function is obtained from the complete data fusion framework. Asserting that t...
A reversible data hiding in the encrypted domain (RDH-ED) aims to hide data within encrypted images, protecting its content, while allowing additional information to be distributed. This paper presents a complete separable RDH-ED scheme, whose main c...
Multi-platform geospatial data synergy is critical for complete and reliable surveys. This study investigates various methods for combining data from terrestrial laser scanning (TLS), orthophotos, databases of topographic objects, utility databases,...
In a future where home health care is no longer an information silo, patient information will be communicated along transitions in care to improve care. Evidence-based practice in the United States supports home health care patients to see their prim...
Electromagnetic data annotation is one of the most important steps in many signal processing applications, e.g., radar signal deinterleaving and radar mode analysis. This work considers cooperative electromagnetic data annotation from multiple reconn...
Our goal was to develop and characterize a Natural Language Processing (NLP) algorithm to extract Eastern Cooperative Oncology Group Performance Status (ECOG PS) from unstructured electronic health record (EHR) sources to enhance observational datase...
This study proposes a novel deep learning framework for predicting the shear capacity of slender reinforced concrete (RC) beams without shear reinforcement. The proposed approach employs convolutional neural networks and autoencoders to transform str...
The integration of user-generated content made in a collaborative environment is being increasingly considered a valuable input to reference maps, even from official map agencies such as USGS and Ordnance Survey. In Brazil, decades of lack of investm...
Global warming is a leading world issue driving the common social objective of reducing carbon emissions. People have witnessed the melting of ice and abrupt changes in climate. Reducing electricity usage is one possible method of slowing these chang...
Nowadays, Volunteered Geographic Information (VGI) has increasingly gained attractiveness to both amateur users and professionals. Using data generated from the crowd has become a hot topic for several application domains including transportation. Ho...
As the number of civil aerial vehicles increase explosively, spectrum scarcity and security become an increasingly challenge in both the airspace and terrestrial space. To address this difficulty, this paper presents an unmanned aerial vehicle-assist...
Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated...
Due to financial or administrative constraints, access to official spatial base data is currently limited to a small subset of all potential users in the field of spatial planning and research. This increases the usefulness of Volunteered Geographic...
Measurement is a typical way of gathering information about an investigated object, generalized by a finite set of characteristic parameters. The result of each iteration of the measurement is an instance of the class of the investigated object in th...
Landslide displacement prediction is a challenging research task that can help to reduce the occurrence of landslide disasters. The frequent occurrence of extreme weather increases the probability of landslides, and the subsequent increase in the sup...
Data completeness is one of the most common challenges that hinder the performance of data analytics platforms. Different studies have assessed the effect of missing values on different classification models based on a single evaluation metric, namel...
The quality assurance of publication data in collaborative knowledge bases and in current research information systems (CRIS) becomes more and more relevant by the use of freely available spatial information in different application scenarios. When i...
2 March 2022
Public health agencies routinely collect time-referenced records to describe and compare foodborne outbreak characteristics. Few studies provide comprehensive metadata to inform researchers of data limitations prior to conducting statistical modeling...
A long-standing challenge for the structural health monitoring (SHM) community is the masking effect of environmental variability, typically addressed by orthogonal projection (OP)-based data normalization to isolate the influence of environmental va...
Due to the low cost and easy deployment, self-supervised depth completion has been widely studied in recent years. In this work, a self-supervised depth completion method is designed based on multi-modal spatio-temporal consistency (MSC). The self-su...
Data sharing helps to make full use of each other’s data and enable the digital economy. With the gradual rise of corporate data sharing, the frequent occurrence of data leakage events highlights the dilemma of data sharing, leakage and supervi...
Due to the sparsity of point clouds obtained by LIDAR, the depth information is usually not complete and dense. The depth completion task is to recover dense depth information from sparse depth information. However, most of the current deep completio...
Ocean Island data are essential to the conservation and management of islands and coastal ecosystems, and have also been adopted by the United Nations as a sustainable development goal (SDG 14). Currently, two categories of island datasets, i.e., glo...
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