The widespread use of data makes privacy protection an urgent problem that must be addressed. Anonymity is a traditional technique that is used to protect private information. In multi-source data scenarios, if attackers have background knowledge of...
Due to the weak signal power and the publicly known structure of civil signals, Global Navigation Satellite Systems (GNSSs) face an increasingly severe threat from spoofing interference. Constrained by inherent limitations such as physical boundaries...
Transfer learning can enhance classification performance of a target domain with insufficient training data by utilizing knowledge relating to the target domain from source domain. Nowadays, it is common to see two or more source domains available fo...
Traffic flow prediction is a vital component of Intelligent Transportation Systems (ITSs), playing a key role in proactive traffic management and the optimization of urban mobility. However, the complex spatial–temporal dependencies, dynamic va...
This paper investigates the design of overlapped chunked codes (OCC) for multi-source multi-relay networks where a physical-layer network coding approach, compute-and-forward (CF) based on nested lattice codes (NLC), is applied for the simultaneous t...
Direction-of-arrival (DOA) estimation remains difficult when the source count is unknown, the signal-to-noise ratio (SNR) is low, or several sources are closely spaced. This paper proposes the Forward Sort-and-Gather Alignment Network (FSA-Net) for j...
We present the workflow for numerical reservoir simulation of supercritical multi-source and multi-component steam injection for offshore heavy oil development. We have developed unique techniques in a commercial reservoir simulator to implement the...
Multi-source image fusion is very important for improving image representation ability since its essence relies on the complementarity between multi-source information. However, feature-level image fusion methods based on the convolution neural netwo...
The primary pollutants emitted from mobile sources have become one of the main sources of urban air pollution. In this study, the primary pollutants CO, HC, NOx and PM from mobile sources in Zibo city, China are studied. Firstly, the localized mobile...
In recent years, many radioactive sources have been lost or stolen during use or transportation. When the radioactive source is lost or stolen, it is challenging but imperative to quickly locate the source before it causes damage. Nowadays, source se...
Rotating machinery is essential to modern industrial systems, where rolling bearings play a critical role in ensuring mechanical stability and operational efficiency. Failures in bearings can result in serious safety risks and significant financial l...
The gravity navigation reference map is a foundational element of gravity matching-aided navigation systems, as it directly determines positioning accuracy and overall navigation performance. To improve fused gravity anomalies and reduce reliance on...
This paper presents an automatic optimization system for the heat source layout of multi-chip modules, referred to as IOS. The system aims to optimize the heat source layout of multi-chip modules through the integration of multiple software tools. Th...
Time Difference of Arrival (TDOA)-based localization is widely used for its stability and high accuracy. However, in multi-source scenarios, TDOA measurements from multiple sources become entangled, making it difficult to separate and correctly assoc...
In recent years, the field of multi-source navigation data fusion has witnessed substantial advancements, propelled by the rapid development of multi-sensor technologies, Artificial Intelligence (AI) algorithms and enhanced computational capabilities...
In response to the application limitations of single-source navigation systems for their susceptibility to interference, insufficient positioning accuracy and limited scenario adaptability in complex environments, as well as the increasingly complex...
Transfer learning (TL) has been employed in electroencephalogram (EEG)-based brain–computer interfaces (BCIs) to enhance performance for cross-session and cross-subject EEG classification. However, domain shifts coupled with a low signal-to-noi...
Multi-source information fusion technology is a kind of information processing technology which comprehensively processes and utilizes multi-source uncertain information. It is an effective scheme to solve complex pattern recognition and improve clas...
Existing studies on non-destructive visual inspection of wheat kernels mainly focus on single-task variety or defect recognition, limiting their ability to jointly exploit complementary surface information, disentangle source-related and quality-rela...
Accurate carbon price forecasting is essential for market stability, regulatory assessment, and risk management in emission trading systems. However, existing approaches find it challenging to extract informative signals from high-dimensional multi-s...
As we move into the information age, the amount of data in various fields has increased dramatically, and data sources have become increasingly widely distributed. The corresponding phenomenon of missing data is increasingly common, and it leads to t...
The development of material science in the manufacturing industry has resulted in a huge amount of material data, which are often from different sources and vary in data format and semantics. The integration and fusion of material data can offer a un...
Supercritical multi-source, multi-component thermal fluid is a heavy oil thermal recovery method independently developed by China National Offshore Oil Co., Ltd (Beijing, China). It uses waste liquid at the production end of the production well as th...
Software-Defined Networking (SDN) is the next generation network architecture with exciting application prospects. The control function in SDN is decoupled from the data forwarding plane, hence it provides a new centralized architecture with flexible...
Geometric distortions and intensity differences always exist in multi-source optical satellite imagery, seriously reducing the similarity between images, making it difficult to obtain adequate, accurate, stable, and well-distributed matches for image...
The utilization of optical and synthetic aperture radar (SAR) multi-source data to obtain better land classification results has received increasing research attention. However, there is a large property and distributional difference between optical...
Fuzzy control theory has been extensively used in the construction of complex fuzzy inference systems. However, we argue that existing fuzzy control technologies focus mainly on the single-source fuzzy information system, disregarding the complementa...
Synthetic Aperture Radar Interferometry (InSAR) has demonstrated significant advantages in detecting active landslides. The proliferation of computing technology has enabled the combination of InSAR and deep learning, offering an innovative approach...
Robust and efficient multi-source image matching remains a challenging task due to nonlinear radiometric differences between image features. This paper proposes a pixel-level matching framework for multi-source images to overcome this issue. Firstly,...
Open-source vulnerability evidence is distributed across vulnerability databases, project advisories, version records, code repositories, issue/PR threads, proofs of concept, and tests. These artifacts may share upstream sources, apply to different s...
Power transformers play a critical role in power systems, and the early detection of their faults and defects, accounting for over 30%, can be achieved through abnormal sound analysis. Sound source localization based on microphone arrays has proven e...
To address the issue of integrity monitoring for a multi-source information fusion navigation system, a theoretical framework of two-level integrity monitoring is proposed. Firstly, at the system level, a system-integrity-monitoring method based on t...
Multi-source spatio-temporal data analysis is an important task in the development of smart cities. However, traditional data analysis methods cannot adapt to the growth rate of massive multi-source spatio-temporal data and explain the practical sign...
Smartphones with integrated sensors play an important role in people’s lives, and in advanced multi-sensor fusion navigation systems, the use of individual sensor information is crucial. Because of the different environments, the weights of the...
This article presents AgoraAI, an open-source framework designed to enable dynamic, multi-participant conversations by integrating Multi-Persona Orchestration within a shared conversational environment. Unlike traditional single-agent Large Language...
Multi-project parallelism is an important feature of open source communities (OSCs), and multi-project collaboration among users is a favorable condition for an OSC’s development. This paper studies the robustness of this type of community. Bas...
The increasing uncertainties and model computational complexity of large-scale power system state estimation have led to the emergence of a class of multi-source metrology devices to provide vector data for the grid to improve the observability. Cons...
Screw pumps’ faulty working conditions affect the stability of oil production. At project sites, different sensors are used simultaneously to collect multi-dimensional signals; the data fault labels and location are not clear, and how to compre...
Multiple sound source separation in a reverberant environment has become popular in recent years. To improve the quality of the separated signal in a reverberant environment, a separation method based on a DOA cue and a deep neural network (DNN) is p...
Bioimpedance measurements have become a useful technique in the past several years in biomedical engineering. Especially, multi-channel measurements facilitate new imaging and patient monitoring techniques. While most instrumentation research has foc...
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In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an e...
Wind power forecasting is a typical high-dimensional and multi-step time series prediction problem. Data-driven prediction methods using machine learning show advantages over traditional physical or statistical methods, especially for wind farms with...
In modern industries, bearings are often subjected to challenges from environmental noise and variations in operating conditions during their operation, which affects existing fault diagnosis methods that rely on signals from single types of sensors....
The phrase “Multi-Power System (MPS)” refers to an application that combines different energy conversion technologies to meet a specific energy need. These integrated power systems are rapidly being lauded as essential for future decarbon...
Efficient diagnosis of apple diseases and pests is crucial to the healthy development of the apple industry. However, the existing single-source image-based classification methods have limitations due to the constraints of single-source input image i...
The development and utilization of urban underground space represents a crucial strategy for achieving sustainable urban development. Three-dimensional (3D) geological models provide a data foundation and technical support for research in urban plann...
Accurate and efficient soybean yield prediction is essential for ensuring food security and optimizing agricultural management. Remote-sensing approaches based on a single phenological stage or sensor may not fully capture the physiological and struc...
Multi-source, combined water supply models play an increasingly important role in solving regional water supply problems. At present, in the area of regional water supply, models are mainly used to study the problem of overall water guarantee rate, a...
A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in...
A novel multi-source energy harvester based on solar and radioisotope energy sources is designed and simulated in this work. We established the calculation formulas for the short-circuit current and open-circuit voltage, and then studied and analyzed...
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