A Multidimensional Data Base is an essential element of decision support, which allows to process complex queries. In this paper, a multilevel distributed Data Model for MDDB is presented. Metadata for MDDB on relations is introduced. To improve effi...
Wind energy has been widely used in recent decades to achieve green and sustainable development. However, wind speed prediction in wind farm clusters remains one of the less studied areas. Spatial features of cluster data of wind speed are not fully...
The massive Internet of Things (IoT) connecting various types of intelligent sensors for goods tracking in logistics, environmental monitoring and smart grid management is a crucial future ICT. High-end security and low power consumption are major re...
To address the difficulty of detecting on-orbit faults of spacecraft under complex operating conditions in time, rational monitoring and assessment of spacecraft health status are essential for ensuring its safe, stable, and reliable operation. Consi...
Modern mobile networks exhibit a complex heterogeneous structure. To enhance the Quality of Service (QoS) in these networks, intelligent control mechanisms should be implemented. These functions are based on the processing of large amounts of data an...
In recent years, with the rapid development of intelligent technology, information security and privacy issues have become increasingly prominent. Epidemiological survey data (ESD) research plays a vital role in understanding the laws and trends of d...
Carbon emissions caused by the massive consumption of energy have brought enormous pressure on the Chinese government. Accurately and rapidly characterizing the spatiotemporal characteristics of Chinese city-level carbon emissions is crucial for poli...
How to use multi-dimensional time series data is a huge challenge for big data analysis. Multiple trajectories of medical use in electronic medical data are typical time series data. Although many artificial-intelligence techniques have been proposed...
In China, tourism development is a crucial approach to poverty alleviation. With the consolidation of poverty alleviation achievements and the promotion of rural revitalization, it is of great significance to explore the relationship between tourism...
False data injection attacks change the control effect of automatic generation control systems, which may cause a destructive impact on power systems. In this paper, the data from the regular operation of a system and the data from false data injecti...
The increasing use of mobile devices and the growing popularity of location-based ser-vices have generated massive spatiotemporal data over the last several years. While it provides new opportunities to enhance our understanding of various urban dyna...
Aiming at the problem that the degradation mechanism of lithium-ion batteries is complex during aging and that a single feature is difficult to fully characterize the battery state of health (SOH), this paper proposes an SOH prediction method for lit...
Pest early warning technology is part of the prerequisite for the timely and effective control of pest outbreaks. Traditional pest warning system with artificial mathematical statistics, radar, and remote sensing has some deficiency in many aspects,...
A novel visualization technique is proposed for the sum of ranking differences method (SRD) based on parallel coordinates. An axis is defined for each variable, on which the data are depicted row-wise. By connecting data, the lines may intersect. The...
As widely adopted privacy models in privacy-preserving data publishing (PPDP), k-anonymity and ℓ-diversity have been extensively studied by researchers to enable the release of useful information while preserving data privacy. However, existing...
Currently, deep reinforcement learning has been widely applied to energy system optimization and scheduling, and the DRL method relies more heavily on historical data. The lack of historical operation data in new integrated energy systems leads to in...
In these days, when complex, IT-controlled systems have found their way into many areas, models and the data on which they are based are playing an increasingly important role. Due to the constantly growing possibilities of collecting data through se...
Monitoring the condition of rotating machinery, especially planetary gearboxes, is a challenging problem. In most of the available approaches, diagnostic procedures are related to advanced signal pre-processing/feature extraction methods or advanced...
The composition of high rockfill dam materials is complex, and the mechanical parameters are uncertain and correlated in unknown ways due to the influences of the environment and construction, leading to complex deformation mechanisms in the dam&ndas...
A major challenge in structural health monitoring (SHM) is the efficient handling of big data, namely of high-dimensional datasets, when damage detection under environmental variability is being assessed. To address this issue, a novel data-driven ap...
In the realm of Ceph distributed storage systems, ensuring swift and symmetrical data recovery during severe data corruption scenarios is pivotal for data reliability and system stability. This paper introduces an innovative FPGA-based Multi-Dimensio...
The recognition of defects in the solder paste printing process significantly influences the surface-mounted technology (SMT) production quality. However, defect recognition via inspection by a machine has poor accuracy, resulting in a need for the m...
Due to the poor visibility of the deep-sea environment, acoustic signals are often collected and analyzed to explore the behavior of marine species. With the progress of underwater signal-acquisition technology, the amount of acoustic data obtained f...
Location fingerprinting using Received Signal Strength Indicators (RSSIs) has become a popular technique for indoor localization due to its use of existing Wi-Fi infrastructure and Wi-Fi-enabled devices. Artificial intelligence/machine learning techn...
In a situation where cities are increasingly being developed vertically and complexly, a novel approach for analyzing vertical urban functional patterns is proposed. For this purpose, a multi-dimensional GDC (Geo Data Cube) consisting of spatial and...
This study set out to extract the charging characteristics of an electrical vehicle (EV) from massive real operating data. Firstly, an unsupervised learning method based on self-organizing map (SOM) is developed to deal with the power supply side dat...
Although measurements of urban shrinkage in China have received much attention, most have relied on statistical yearbook data based on political–administrative city boundaries, and remote-sensing-based quantification is mainly one-dimensional....
Full waveform inversion (FWI) comprehensively utilizes phase and amplitude information of seismic waves to obtain high-resolution subsurface medium parameter models, applicable to both active-source and passive-source seismic data. Passive-source sei...
Urban function labels in multi-dimensional geo-data cubes (GDCs) assign a single dominant function to each voxel, discarding within-voxel composition. This study extends multi-dimensional grid-point (MDGP) scaling from isotropic two-dimensional raste...
During the exploration and visualization of big spatio-temporal data, massive volume poses a number of challenges to the achievement of interactive visualization, including large memory consumption, high rendering delay, and poor visual effects. Rese...
2 December 2021
Under the influence of complex urbanization, improving the carbon emission efficiency (CEE) plays an important role in the construction of low-carbon cities in China. Based on the panel data of 283 prefectural-level cities in China from 2005 to 2017,...
With the rapid development of big data and artificial intelligence technologies, the era of Industry 4.0 has driven large open-pit mines towards digital and intelligent transformation. This is particularly true in mature mining areas such as the Yans...
This research presents a large-scale thematic analysis of 66,002 Slovak university thesis abstracts, aimed at identifying, categorizing, and visualizing research trends across multiple academic disciplines. Using BERTopic for unsupervised topic model...
Similar time series search is one of the most important time series mining tasks in our daily life. As recent advances in sensor technologies accumulate abundant multi-dimensional time series data associated with multivariate quantities, it becomes a...
Distributed multi-dimensional classification, where multiple nodes over a network induce a multi-dimensional classifier based on their own local data and a little information exchanged from neighbors, has received extensive attention in the academic...
This work studies the feasibility of a novel two-step algorithm for infrastructure and object positioning, using pairwise distances. The proposal is based on the optimization algorithms, Scaling-by-Majorizing-a-Complicated-Function and the Limited-Me...
Currently, a significant focus has been established on the privacy protection of multi-dimensional data publishing in various application scenarios, such as scientific research and policy-making. The K-anonymity mechanism based on clustering is the m...
In recent years, cloud computing and edge computing have flourished, establishing data centers as pivotal hubs for information exchange. However, the security for the interconnection of these data centers faces increasingly severe challenges. Traditi...
10 February 2023
In this paper, we examined the impact of financial development on renewable energy consumption from a global perspective based on a dynamic panel model and panel data of 103 economies. We conducted the research from the different levels of financial...
As one of the world’s most crucial crops, the potato is an essential source of nutrition for human activities. However, several diseases pose a severe threat to the yield and quality of potatoes. Timely and accurate detection and identification...
Ballast serves a vital structural function in supporting railroad tracks under continuous loading. The degradation of ballast can result in issues such as inadequate drainage, lateral instability, excessive settlement, and potential service disruptio...
Safety is the foundation of urban sustainable development. The urban construction and operation process involves a large amount of multidimensional time series data. By detecting anomalies in these multidimensional time subsequences (MTSs), decision...
23 December 2022
Getting rid of multidimensional poverty is both the people’s wish and the direction of governance. Based on 2018 China Household Tracking Survey (CFPS) data, this paper identifies household multidimensional poverty in rural areas using a combin...
A new fractional Brownian vector field (FBVF) is created for modeling multidimensional and multivariate fractal data. It is shown that the FBVF is a multidimensional and multivariate generalization of the classical Kolmogorov–Wiener process, al...
3 February 2023
People with disabilities are more likely than individuals without disabilities to face higher levels of deprivation and multidimensional poverty, and those deprivations might be associated with the extra costs of living with a disability. However, th...
The rapid growth of industry and the economy has contributed to a tremendous increase in traffic in all urban areas. People face the problem of traffic congestion frequently in their day-to-day life. To alleviate congestion and provide traffic guidan...
In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand...
The evaporation duct height (EDH) can reflect the main characteristics of the near-surface meteorological environment, which is essential for designing a communication system under this propagation mechanism. This study proposes an EDH prediction net...
Under laboratory conditions for recording a small amount of data, the characteristics of the phenomena distribution become a limitation of machine learning and advanced deep learning concepts for the diagnosis and localization of mechanical wear faul...
Extreme rainfall events are significant manifestations of climate change, causing substantial impacts on urban infrastructure and public life. This study takes the extreme rainfall event in Beijing in 2023 as the background and utilizes data from Sin...
of 52