In the area of network analysis, centrality metrics play an important role in defining the “most important” actors in a social network. However, nowadays, most types of networks are dynamic, meaning their topology changes over time. The connection we...
Understanding a learner’s resources as a system of interacting components, the success of a learning process is determined by the effectiveness of their interactions. Theoretical assumptions and empirical findings clearly show the importance of...
In system processing, video inevitably suffers from distortion, which leads to quality degradation and affects the user experience. Therefore, it is of great importance to design an accurate and effective objective video quality assessment (VQA) meth...
With the active promotion of the “carbon peaking and carbon neutrality” goals, science and technology finance (STF) is the important driving force of low-carbon development, and financial networks facilitate the aggregation and transforma...
With the rapid acceleration of industrialization and urbanization in China, PM2.5 pollution has emerged as a major challenge to public health and sustainable development of the society and economy. At the interprovincial level, PM2.5 exhibits a compl...
Global forest-product trade faces severe disruptions from external shocks, necessitating robust forecasting and risk assessment tools. To capture the complex, nonlinear dynamics of the forest bioeconomy, this study constructs a comprehensive panel co...
Automotive dashboard cameras are widely used to record driving events and often serve as critical evidence in accident investigations and insurance claims. However, the availability of free and low-cost editing tools has increased the risk of video t...
Motor current signature analysis (MCSA) enables non-invasive condition monitoring of three-phase induction motors, but most published studies use short laboratory records with artificially seeded faults and report only a discrete fault label without...
Digital Security by Design (DSbD) is an initiative supported by the UK government aimed at transforming digital technology to deliver necessary digital resilience and prosperity across the UK. As emerging challenges in the field of digital security e...
Hydrological series are largely characterized by a strong random component in their behavior. More noticeable changes in the behavior patterns of rainfall/runoff temporal series are recently being observed. These modifications are not a trivial issue...
Landslide displacement prediction is an essential base of landslide hazard prevention, which often needs to establish an accurate prediction model. To achieve accuracy prediction of landslide displacement, a displacement prediction model based on a s...
Low Earth orbit (LEO) satellites that can be used as computing nodes are an important part of future communication networks. However, growing user demands, scarce channel resources and unstable satellite–ground links result in the challenge to...
As dynamic systems, social networks exhibit continuous topological changes over time, and are typically modeled as temporal networks. In order to understand their dynamic characteristics, it is essential to investigate temporal community detection (T...
We consider an ensemble of drones moving in a two-dimensional domain, each one of them carrying a communication device, and we investigate the problem of information transfer in the swarm when the transmission capabilities are short range. The proble...
Persistent late-time variation can remain in physics-informed neural network (PINN) solutions after the governing transient has effectively decayed, while conventional error norms do not reveal whether this variation has a systematic temporal–f...
Spatio-temporal characterization analysis plays a key role in spatio-temporal data mining tasks such as social relationship inference, traffic flow prediction, and spatio-temporal graph node classification. Although traditional numerical simulation m...
Analyzing network traffic over time is crucial for understanding the changes in network activity. To properly examine network traffic patterns over time, multiple network events in each timestamp need to be converted to time series data. In this stud...
Social network analysis (SNA) is a quantitative approach to study relationships between individuals. Current SNA methods use static models of organizations, which simplify network dynamics. To better represent the dynamic nature of clinical care, we...
Despite the growing number of publications using the value network approach to analyze agro-industrial competitiveness, knowledge gaps persist in other food production sectors. The objective of this study is to analyze, through bibliometric technique...
This study aims to predict new technologies by analyzing patent data and identifying key technology trends using a Temporal Network. We have chosen big data-based smart logistics technology as the scope of our analysis. To accomplish this, we first e...
The objective of this work is to perform a temporal comparative analysis in a network of companies in the furniture sector, in Santa Catarina, southern Brazil, presenting drivers through circular economy modeling. The study was performed applying the...
Bogotá is the capital of Colombia and represents the most important urban center in the country. Bogotá’s population and economic growth have accelerated exponentially in recent years and this growth has brought with it a variety...
Non-invasive methods used for PH detection in clinical practice have several limitations. The combination of high spatiotemporal sensitivity magnetocardiography (MCG) and artificial intelligence algorithms may offer an accurate approach for PH detect...
Traditional village tourism is an effective path to rural revitalization and an excellent way to preserve traditional sceneries and cultural heritage. However, research on the subject matter has been limited. To address some of the current research g...
Ecological network resilience is an important indicator for evaluating whether regional ecosystems can maintain structural connectivity and functional stability under external disturbance. However, long-term changes in ecological network structure an...
Profiling side-channel attacks based on deep learning can recover cryptographic information from power-consumption traces, but their effectiveness may be reduced when desynchronisation displaces informative leakage across temporal positions. This stu...
Solar irradiance forecasting is fundamental and essential for commercializing solar energy generation by overcoming output variability. Accurate forecasting depends on historical solar irradiance data, correlations between various meteorological vari...
Accurate and timely estimation of grass yield is crucial for understanding the ecological conditions of grasslands in the Mongolian Plateau (MP). In this study, a new artificial neural network (ANN) model was selected for grassland yield inversion af...
This paper presents an end-to-end system for the automatic summarization of football matches through temporally accurate event spotting across six action categories: goal, card, substitution, kick-off, direct free-kick, and corner. These six classes...
As a green and sustainable travel mode, the bikeshare plays an important role in solving the “last-mile” problem. The new dockless bikeshare system (DBS) is widely favored by travelers, and the traditional docked bikeshare system (BS) is...
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Give...
This study presents a novel framework that integrates Vision Graph Neural Networks (ViGs) with supervised contrastive learning for enhanced spectro-temporal image analysis of speech signals in Parkinson’s disease (PD) detection. The approach in...
The transformation of resource-exhausted urban land is an urgent problem for sustainable urban development in the world today. Obtaining the urban land use type and analyzing the changes in their land use can lead to better management of the relation...
Link prediction is recognized as a crucial means to analyze dynamic social networks, revealing the principles of social relationship evolution. However, the complex topology and temporal evolution characteristics of dynamic social networks pose signi...
The countries in the Belt and Road Initiative (BRI) significantly influence global carbon emissions, and the spatial correlation and driving mechanisms of their emissions are crucial for regional emission reduction and global climate governance. This...
This study presents a data-driven and explainable artificial intelligence (XAI) framework for quantitatively analyzing research trends in the seismic performance of timber structures. Unlike conventional bibliometric approaches based on descriptive s...
This paper uses network analysis to study the geo-localization decisions of new organic dairy farm operations in the USA between 2002 and 2015. Given a dataset of organic dairy certifications we simulated spatio-temporal networks based on the locatio...
Proton exchange membrane fuel cells (PEMFCs) are ideal for fuel cell vehicles due to their high specific power, rapid start-up, and low operating temperatures. However, their limited lifespan presents a challenge for large-scale deployment. Accurate...
With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (Dosidicus gigas). This can help reduce fuel costs and provide hi...
Seizure detection based on intracranial electroencephalography (iEEG) signals is a relevant task in the analysis of epilepsy. In this context, it is not only important to achieve high predictive performance but also to ensure explainability, which al...
Accurate traffic flow forecasting is a fundamental component of Intelligent Transportation Systems and proactive urban mobility management. However, the inherent complexity of urban traffic flow, characterized by non-stationary dynamics and multi-sca...
Higher education institution campuses have been growing in size to become small cities that encompass all the infrastructures and offer many services to the university community. In order to achieve sustainable growth, it is necessary to take into ac...
4 March 2021
Based on the panel data of 41 cities in the Yangtze River Delta from 2008 to 2017, this paper constructs an evaluation indicators system for urban tourism eco-efficiency. By measuring the tourism eco-efficiency in the Yangtze River Delta urban agglom...
Since 2015, China has witnessed a rapid increase in new energy vehicle (NEV) market penetration, achieving global leadership in this sector. This study employs social network analysis (SNA) and Granger causality tests to examine how policy coordinati...
Under the rapid advancements in information technology, the complex network characteristics of agricultural product trade relationships among global economies have exhibited increasing prominence. This study takes the soybean trade market as an empir...
This paper presents a comprehensive time-series analysis framework leveraging the Temporal Fusion Transformer (TFT) architecture to address the challenge of multi-horizon forecasting in complex ecological systems, specifically focusing on global fish...
Accurate air quality prediction is paramount in safeguarding public health and addressing air pollution control. However, previous studies often ignore the geographic similarity among different monitoring stations and face challenges in dynamically c...
Based on social network analysis (SNA) and the modified Boston Matrix (also known as Market Growth Rate—Relative Market Share Matrix or Four Quadrant Analysis, which was developed by the Boston Consulting Group (BCG) in the early 1970s.), this...
Group activity recognition is a central theme in many domains, such as sports video analysis, CCTV surveillance, sports tactics, and social scenario understanding. However, there are still challenges in embedding actors’ relations in a multi-pe...
Cross-border greenfield investment in the financial services sector is increasingly understood not as isolated flows, but as a complex, dynamic global system. This systemic perspective is essential for understanding its holistic structure and evoluti...
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