Efficient estimation methods for simultaneous autoregressive (SAR) models with missing data in the response variable have been well explored in the literature. A common practice is introducing measurement error into SAR models to separate the noise c...
A rapid growth in spatial open datasets has led to a huge demand for regression approaches accommodating spatial and non-spatial effects in big data. Regression model selection is particularly important to stably estimate flexible regression models....
The modeling, analysis and visualization of dynamic geospatial phenomenahas been identified as a key developmental challenge for next-generation GeographicInformation Systems (GIS). In this context, the envisaged paradigmatic extensions tocontemporar...
Typically, the traditional bootstrap methods for parameter inference of spatial error models suffer from high computational costs, so this study proposes fast cluster bootstrap methods for spatial error models to deal with the dilemma. The key idea i...
Three-dimensional (3D) pipe network modeling plays an essential part in high performance-based smart city applications. Given that massive 3D pipe networks tend to be difficult to manage and to visualize, we propose in this study a hybrid framework f...
Virtual geographic environments long simulated real-world scenarios in urban planning, monument preservation, city infrastructure management, education, and entertainment. Their web-based visualisation and distribution made these environments widely...
With the exponential growth of user-generated content on video-sharing platforms, the challenge of facilitating efficient searching and browsing of videos has garnered significant attention. To enhance users’ ability to swiftly locate and revie...
Figure Ground Organization (FGO)-inferring spatial depth ordering of objects in a visual scene-involves determining which side of an occlusion boundary is figure (closer to the observer) and which is ground (further away from the observer). A combina...
Selective catalytic reduction (SCR) is one of the most efficient methods to reduce NOx emissions from coal-fired power plants. This paper deals with an optimal design tower type SCR-deNOx facility for a 1000 MW coal-fired power plant. Combined with c...
This paper introduces a novel BIM-based computational workflow that embeds spatial analysis directly within the Building Information Modelling (BIM) environment to support the evaluation and design of hospital emergency department (ED) layouts. Conve...
Accurate object detection and measurement within indoor environments—particularly unfurnished or minimalistic spaces—pose unique challenges for conventional computer vision methods. Previous research has been limited to small objects that...
Achieving robust environmental responsiveness in early stage architectural spatial layout design remains a critical challenge under the imperatives of global carbon neutrality and climate-adaptive building practice. Conventional parametric design and...
Efficient and accurate license plate recognition (LPR) in unconstrained environments remains a critical challenge, particularly when confronted with skewed imaging angles and the limited computational capabilities of edge devices. In this study, we p...
Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of s...
Transcutaneous electrical stimulation (TES) is a non-invasive technique that delivers electrical currents through the skin to modulate peripheral neural and muscular activity. However, conventional surface stimulation often exhibits limited spatial s...
As a critical infrastructure carrier underpinning the cross-regional circulation of data elements within socioeconomic systems, intelligent computing centres (ICCs) confront a pivotal practical challenge amid the transition to a green economy: whethe...
Most contemporary crop yield models focus on a small time window, operate on a plot location, or do not include the effects of the changing environment, which makes it difficult to use these models to assess the agricultural sustainability for past s...
The impact of COVID-19 across the United States (US) has been heterogeneous, with rapid spread and greater mortality in some areas compared with others. We used geographically-linked data to test the hypothesis that the risk for COVID-19 was defined...
Understanding how the human brain processes and interprets multimedia content represents a frontier challenge in neuroscience and artificial intelligence. This study introduces a novel approach to decode semantic information from electroencephalogram...
Poland is the most coal-dependent economy and one of the biggest polluters in the EU. In order to alleviate this problem, meet CO2 emission requirements set by EU, and improve the country’s energy security, Poland decided to introduce nuclear p...
Motor imagery (MI)-based brain–computer interfaces (BCIs) have led to great interest as a result of their potential use in neurorehabilitation, assistive robotics, and human–computer interaction. However, decoding electroencephalographic...
Digital Elevation Model (DEM) resolution plays a critical role in hydraulic flood modelling by influencing inundation accuracy, spatial precision and computational efficiency. However, limited studies have simultaneously evaluated both inundation acc...
The safety of mandibular anesthesia is directly dependent on a precise understanding of the spatial relationships in the pterygomandibular space, particularly the risk of injury to the highly vascularized pterygoid venous plexus (PVP). In vivo studie...
27 November 2022
The global COVID-19 pandemic has taken a heavy toll on health, social, and economic costs since the end of 2019. Predicting the spread of a pandemic is essential to developing effective intervention policies. Since the beginning of this pandemic, man...
The European Space Agency (ESA) defines Earth observation (EO) Level 2 information product the stack of: (i) a single-date multi-spectral (MS) image, radiometrically corrected for atmospheric, adjacency and topographic effects, with (ii) its data-der...
Augmented reality has a wide range of applications in many areas that can extend the study of real objects into the digital world, including stomatology. Real dental objects that were previously examined using their plaster casts are often replaced b...
The integration of computational intelligence and augmented reality has become increasingly prevalent in dental practices. Three-dimensional (3D) printing techniques have now become routine in orthodontics, prosthetics, and maxillofacial surgery. The...
This work presents a numerical mesh generation method for 3D urban scenes that could be easily converted into any 3D format, different from most implementations which are limited to specific environments in their applicability. The building models ha...
This paper devises an algorithm for finding the minimal set of axial lines that can represent a geometry of building and urban layout in two dimensions. Although axial lines are useful to analyze spatial configuration in the Space Syntax, existing me...
Land, as the foundation of all productive activities, plays a crucial role in achieving high-quality development across regions. China’s current land allocation model, which focuses on land quota distribution, has several drawbacks and does not...
Observing state variables, fluxes, and key properties in terrestrial ecosystems should not be seen as disjointed, but rather as fruitfully complementary to ecosystem dynamics modeling. This intertwined view should also take the organization of the mo...
A spatially-distributed continuous mathematical model of solid tumor growth and treatment by fractionated radiotherapy is presented. The model explicitly accounts for three time and space-dependent factors that influence the efficiency of radiotherap...
It has been hypothesized that solid tumors with invasive type of growth should possess intrinsic resistance to antiangiogenic therapy, which is aimed at cessation of the formation of new blood vessels and subsequent shortage of nutrient inflow to the...
The natural environment and our interaction with it are essentially multisensory, where we may deploy visual, tactile and/or auditory senses to perceive, learn and interact with our environment. Our objective in this study is to develop a scene analy...
A continuous mathematical model of non-invasive avascular tumor growth in tissue is presented. The model considers tissue as a biphasic material, comprised of a solid matrix and interstitial fluid. The convective motion of tissue elements happens due...
This article presents an evaluation of the ERDAS IMAGINE Spatial Model Editor from the perspective of effective cognition. Workflow models designed in Spatial Model Editor are used for the automatic processing of remote sensing data. The process step...
Agricultural development across much of sub-Saharan Africa is constrained by the gap in knowledge on site suitability for sustainably expanding irrigable lands to new areas. This study aimed to identify the most suitable sites for promoting small-sca...
(1) Background: It is difficult for accident investigators to objectively determine whether spatial disorientation may have contributed to a fatal airplane accident. In this paper, we evaluate three methods to reconstruct the possible occurrence of t...
Thoracic aortopathies, including aneurysm and dissection, are complex vascular disorders characterized by structural alterations of the aortic wall that disrupt normal haemodynamics. Altered shear stress, turbulent flow, and endothelial dysfunction p...
Accurate assessment of fish feeding intensity is significant for the timely understanding of feeding demands, dynamically adjusting feeding strategies, and reducing aquaculture costs. However, existing methods often rely on superficial visual feature...
High-resolution wind datasets are crucial for ultra-short-term wind forecasting. Penetration of WT installations near urban areas that are constantly changing will motivate researchers to understand how to adapt their models to terrain changes to red...
Transboundary river basins combine spatially continuous ecological processes with nationally differentiated land use, development intensity, and environmental governance, yet it remains unclear how these asymmetries shape landscape ecological risk (L...
Although visual assessments of the built environment have progressed, existing studies frequently evaluate metropolitan spaces as uniform entities. This overlooks the interplay between subjective spatial perception and functional infrastructure acros...
Deep learning models are widely used in autonomous vehicle systems for perception, localization, and decision-making. However, their lack of transparency poses significant challenges in safety-critical environments. This systematic review presents a...
Spatial transcriptomics links gene expression to tissue morphology but is too costly for routine clinical use, motivating prediction of expression from hematoxylin-and-eosin (H&E) images. FViT (Foundation-tokenized Vision Transformer) tokenizes a...
This tutorial takes the reader on a historical and technical journey from the simple Perceptron (1958) to modern Convolutional Neural Networks (CNNs) that dominate spatial data processing (images and video). We start with the Perceptron’s linea...
Accurate spatial–temporal crime prediction is a critical component of proactive public safety governance, yet it remains challenging due to complex dependency structures and severe data sparsity in real-world crime datasets. Most existing metho...
Virtual reality (VR) has emerged as a complex technological domain that demands high levels of realism and interactivity. At the core of this immersive experience lies a broad spectrum of mathematical modeling techniques. This survey explores how mat...
The paper examines the development of forecasting and modeling technologies for environmental processes using classical and quantum data analysis methods. The main focus is on the integration of deep neural networks and classical algorithms, such as...
An important, but overlooked component of disaster managment is raising the awareness and preparedness of potential stakeholders. We show how recent advances in agent-based modeling and geo-information analytics can be combined to this effect. Using...
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