In the rapidly advancing domain of Intelligent Connected Vehicles (ICVs), multimodal Federated Learning (FL) presents a powerful methodology to harness diverse data sources, such as sensors, cameras, and Vehicle-to-Everything (V2X) communications, wi...
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that progressively affects bulbar and limb function. Despite increasing recognition of the disease as a multinetwork disorder characterized by aberrant structural and functional conn...
A retinal vessel analysis is a procedure that can be used as an assessment of risks to the eye. This work proposes an unsupervised multimodal approach that improves the response of the Frangi filter, enabling automatic vessel segmentation. We propose...
Brain connectivity analysis plays a crucial role in unraveling the complex network dynamics of the human brain, providing insights into cognitive functions, behaviors, and neurological disorders. Traditional graph-theoretical methods, while foundatio...
V2X is used for communication between the surrounding pedestrians, vehicles, and roadside units. In the Forward Collision Warning (FCW) of Phase One scenarios in V2X, multimodal modalities and multiple warning stages are the two main warning strategi...
Trajectory prediction of surrounding vehicles is a critical task for connected and autonomous vehicles (CAVs), helping them to realize potential dangers in the traffic environment and make the most appropriate decisions. In a practical traffic enviro...
Multi-modal object re-identification (ReID) is a challenging task that seeks to identify objects across different image modalities by leveraging their complementary information. Traditional CNN-based methods are constrained by limited receptive field...
The diagnosis of attention-deficit/hyperactivity disorder (ADHD) has long relied on subjective scales, lacking objective neuroimaging biomarkers. Static functional connectivity (sFC) and dynamic functional connectivity (dFC), as commonly used metrics...
This study examines coordinated active-power allocation in a DC-coupled photovoltaic (PV) and energy storage system (ESS) with a virtual synchronous generator (VSG) inverter. A rule-based supervisor selects PV maximum power point tracking (MPPT) or t...
This article explores concepts related to connectivity and usership of the Jordan River Parkway Trail (JRPT) and the North Temple corridor—two locations or nodes that link together in a larger transportation network along the west side of Salt...
This study introduces a new metro train demand model that simultaneously captures both aggregate ridership from automated fare collection (AFC) data and disaggregate consideration propensities, using individual survey data from Chennai, India. This j...
This paper presents the latent model-joint embedding predictive architecture (LM-JEPA), a resource-efficient collaborative perception framework for connected and autonomous vehicles that integrates latent predictive representation learning with light...
To enhance the accessibility and efficiency of airports, the concept of airport connectivity is extended to High-Speed Rail (HSR), as major hub airports now have direct access to an HSR station. The traditional hub connectivity index is supplemented...
Rural communities in many low- and middle-income countries (LMICs) remain isolated from reliable access to critical sites and social services due to inadequate transport connectivity. Formal planning approaches to improve rural networked transport in...
Complex diseases often involve distributed interactions among biological regions, physiological systems, imaging phenotypes, and clinical variables that are not fully captured by anatomical proximity, isolated biomarkers, or conventional feature-base...
Real-time monitoring of urban building development provides a basis for urban planning and management. Remote sensing change detection is a key technology for achieving this goal. Intelligent change detection based on deep learning of remote sensing...
Monitoring the curing process of concrete remains a challenging and critical aspect of modern construction, often hindered by labour-intensive, invasive, and inflexible methods. The primary aim of this study is to develop an integrated IoT-enabled pl...
Simultaneous Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) provide a powerful framework for investigating brain dynamics; however, ballistocardiogram (BCG) artifacts in EEG compromise signal quality and limit the asses...
With the advancement of image processing techniques, few-shot learning (FSL) has gradually become a key approach to addressing the problem of data scarcity. However, existing FSL methods often rely on unimodal information under limited sample conditi...
Background: Against the backdrop of global population aging, understanding the mechanisms of age-related cognitive decline has become crucial for improving the health and quality of life in older adults. Methods: This study employed a multimodal appr...
Accurate and real-time traffic and road weather information acquired using connected vehicle (CV) technologies can help commuters perform safe and reliable trips. A nationwide survey of transit operation managers/supervisors was conducted to assess t...
Radar space target recognition is faced with inherent challenges due to complex electromagnetic scattering properties and limited training samples. Conventional single-modality approaches cannot fully characterize targets due to information incomplet...
Ensuring the structural continuity and completeness of road networks in high-resolution remote sensing imagery remains a major challenge for current deep learning methods, especially under conditions of occlusion caused by vegetation, buildings, or s...
As the primary interface for integrating renewable energy sources such as wind and solar power into the grid, inverters are prone to inducing sub-/super-synchronous or medium-to-high-frequency oscillations during grid-connected operation under weak g...
For a new distribution network with energy storage and a flexible multi-state switch (FMSS), several problems of multi-mode operation and switching, such as the unbalance of feeder loads and feeder faults, among others, should be considered. This pap...
The emerging technology of internet of connected vehicles (IoCV) introduced many new solutions for accident prevention and traffic safety by monitoring the behavior of drivers. In addition, monitoring drivers’ behavior to reduce accidents has attract...
Emotion recognition is a key attribute for realizing advances in human–computer interaction, especially when using non-intrusive physiological sensors, such as electroencephalograph (EEG) and electrocardiograph. Although functional connectivity...
Cognitive dysfunction is an important non-motor symptom in amyotrophic lateral sclerosis (ALS) that has a negative impact on survival and caregiver burden. It shows a wide spectrum ranging from subjective cognitive decline to frontotemporal dementia...
As one of the main elements of reinforcement learning, the design of the reward function is often not given enough attention when reinforcement learning is used in concrete applications, which leads to unsatisfactory performances. In this study, a re...
This paper investigates the application of Transit-Oriented Development (TOD) principles to the retrofitting of historic Gulf urban cores through a comparative analysis of Souq Waqif (Doha) and Qasr Al Hokm (Riyadh). The research employs field observ...
Autonomous vehicles rely extensively on onboard sensors to perceive their surrounding environments for motion planning and vehicle control. Despite recent advancements, prevalent perception algorithms typically utilize data acquired from the single h...
Schizophrenia is widely seen as a disorder of dysconnectivity. Neuroimaging studies have examined both structural and functional connectivity in the disorder, but these modalities have rarely been integrated directly. We scanned 29 patients with schi...
The ever-increasing tendency toward economic globalization highlights the importance of sustainable container transport networks to a country’s international trade, especially for an economy that is highly dependent on exports. This paper aims...
In the intelligent assembly of prefabricated concrete column joints based on a multimodal transformer and digital twin, a finite element model is constructed using a digital twin to map physical entities from multiple dimensions, accurately set the m...
The Social Internet of Things (SIoT) connects smart devices into social networks in which they share, forward, and consume visual content on behalf of their owners. As generative models become more capable, the images that circulate among these conne...
Public transit plays a key role in shaping the transportation structure of large and fast growing cities. To cope with high population and employment density, such cities usually resort to multi-modal transit services, such as rail, BRT and bus. Thes...
Sustainable development of transport systems is a common topic of concern and effort in multiple countries, in which reducing carbon emissions is one of the core goals. Multimodal transport is an effective way to achieve carbon emission reduction and...
The extensive research in the field of multimodal biometrics by the research community and the advent of modern technology has compelled the use of multimodal biometrics in real life applications. Biometric systems that are based on a single modality...
Visual target tracking is a fundamental task in computer vision. Combining multi-modal information with tracking leverages complementary information, which improves the precision and robustness of trackers. Traditional multi-modal tracking methods ty...
Most multimodal transit studies use pairwise or multilayer graphs that discard route membership. We construct route-preserving bus–metro hypergraphs for 45 Chinese cities. A route-support rule makes node viability depend on the fraction of inci...
Cross-border multimodal transportation systems are essential for regional connectivity, yet their structural concentration, modal imbalance, community organization, and accessibility differentiation remain insufficiently understood from an entropy pe...
Transit connectivity is a critical indicator for evaluating the transfer efficiency and network performance of hub airports within integrated transport systems. However, conventional connectivity models primarily rely on flight frequency and schedule...
This paper reviews 74 empirical publications that used high-frequency data collection tools to capture facets of small collaborative groups—i.e., papers that conduct Multimodal Collaboration Analytics (MMCA) research. We selected papers publish...
We present a single-capture multimodal bright-field (BF) and quantitative phase imaging (QPI) approach that enables the analysis of large, connected, or extended samples, such as confluent cell layers or tissue sections. The proposed imaging concept...
To solve the multi-ship interaction problem under the scenario of multi-modal ships, this paper designed a ship Mobile Ad hoc Network (MANET) dominated by an autonomous ship. Foremost, we discussed the development and status of autonomous ships, prop...
The optimisation of airport infrastructure capacities lacks adequate tools that would enable airport owners and managers to make strategic decisions related to sustainable development and strengthening multimodal connectivity. Assessing the sustainab...
Introduction: We present here a methodology for morphometric analysis of the substantia nigra (SN), the ventral tegmental area (VTA), the dorsal raphe nucleus (DRN) and their respective structural brain circuits. Methods: Our analyses were based on m...
In many tasks related to an object’s observation or real-time monitoring, the gathering of temporal multimodal data is required. Such data sets are semantically connected as they reflect different aspects of the same object. However, data sets...
The maturity of fruits and vegetables such as tomatoes significantly impacts indicators of their quality, such as taste, nutritional value, and shelf life, making maturity determination vital in agricultural production and the food processing industr...
Assessing plum quality solely based on the external appearance of the peel may lead to inaccurate results. This paper proposes a multimodal data fusion technique based on deep learning, which evaluates plum quality by fusing color image data and spec...
of 16