The embedded visual tracking system has higher requirements for real-time performance and system resources, and this is a challenge for visual tracking systems with available hardware resources. The major focus of this study is evaluating the results...
Kernel density estimation (KDE) is a commonly used method for spatial point pattern analysis, but it is computationally demanding when analyzing large datasets. GPU-based parallel computing has been adopted to address such computational challenges. T...
Due to the complex topological relationship, poor data locality, and data racing problems in unstructured CFD computing, how to parallelize the finite volume method algorithms in shared memory to efficiently explore the hardware capabilities of many-...
Space-based gravitational wave missions such as LISA, Taiji, and Tianqin rely on the time-delay interferometry (TDI) technique to observe low-frequency signals such as Galactic binaries (GBs), massive black-hole binaries, and extreme-mass-ratio inspi...
We present a refinement of the Immersive Parallel Coordinates Plots (IPCP) system for Virtual Reality (VR). The evolved system provides data-science analytics built around a well-known method for visualization of multidimensional datasets in VR. The...
A prevailing way of extracting valuable information from biomedical literature is to apply text mining methods on unstructured texts. However, the massive amount of literature that needs to be analyzed poses a big data challenge to the processing eff...
The majority of complex research problems can be formulated as optimization problems. Particle Swarm Optimization (PSO) algorithm is very effective in solving optimization problems because of its robustness, simplicity, and global search capabilities...
In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with the parallel factor analysis model. Traditional methods, such as scaling, orthogonality constraints, non-negativity constraints, and sparse techniques...
We propose a new strategy for the parallelization of mesh processing algorithms. Our main contribution is the definition of distributed combinatorial maps (called n-dmaps), which allow us to represent the topology of big meshes by splitting them into...
This paper introduces the Accumulated Concept Graph (ACG), a visualization tool based on the quantile method designed to analyze three-way data, including distributional data. Such data often have complex structures that make it difficult to identify...
Water quality data cleaning is important for the management of water environments. A framework for water quality time series cleaning is proposed in this paper. Considering the nonlinear relationships among water quality indicators, support vector re...
Interferometric synthetic aperture radar (InSAR) has achieved great success in various geodetic applications, and its potential for ground deformation measurements on the large scale has attracted increasingly more attention in recent years. The incr...
The order-preserving multiple pattern matching problem is to find all substrings of T whose relative orders are the same for any pattern in a set of patterns. Various sequential algorithms have been studied for the order-preserving multiple pattern m...
Underwater sensor networks have wide application prospects, but the large-scale sensing node deployment is severely hindered by problems like energy constraints, long delays, local disconnections, and heavy energy consumption. These problems can be s...
Calculation of structural features of proteins, nucleic acids, and nucleic acid-protein complexes on the basis of their geometries and studying various interactions within these macromolecules, for which high-resolution structures are stored in Prote...
Clustering algorithms have proven to be a useful tool to extract knowledge and support decision making by processing large volumes of data. Hard and fuzzy clustering algorithms have been used successfully to identify patterns and trends in many areas...
This paper presents a parallel implementation of a non-local transform-domain filter (BM4D). The effectiveness of the parallel implementation is demonstrated by denoising image series from computed tomography (CT) and magnetic resonance imaging (MRI)...
The aim of this paper is to present a mobile agents model for distributed classification of Big Data. The great challenge is to optimize the communication costs between the processing elements (PEs) in the parallel and distributed computational model...
This paper proposes a data-driven model-free robust predictive control strategy for parallel three-level NPC inverters based on finite control set model predictive control (FCS-MPC), focusing on the zero-sequence circulating current (ZSCC) problem un...
Every day, hundreds of thousands of vehicles, including buses, taxis, and ride-hailing cars, continuously generate GPS positioning records. Simultaneously, the traffic big data platform of urban transportation systems has already collected a large am...
Modern architectures make possible development in new algorithms for large data sets and distributed computing. The newly proposed versions can benefit both from faster computing on the multi core architectures, and intelligent programming techniques...
Data collected from the supervisory control and data acquisition (SCADA) system are used widely in wind farms to obtain operation and performance information about wind turbines. The paper presents a three-way model by means of parallel factor analys...
Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the perfor...
Significant computation challenges are emerging as agent-based modeling becomes more complicated and dynamically data-driven. In this context, parallel simulation is an attractive solution when dealing with massive data and computation requirements....
The energy consumption of data center cooling systems is rapidly increasing, necessitating urgent improvements in cooling system performance. This study investigates a pump-driven two-phase cooling system (PTCS) utilizing a parallel-flow heat exchang...
The volume, variety, and velocity of different data, e.g., simulation data, observation data, and social media data, are growing ever faster, posing grand challenges for data discovery. An increasing trend in data discovery is to mine hidden relation...
Nowadays, several environmental applications take advantage of remote sensing techniques. A considerable volume of this remote sensing data occurs in near real-time. Such data are diverse and are provided with high velocity and variety, their pre-pro...
The rapid growth of high-dimensional biometric data requires fast and accurate similarity search methods for real-time applications. This study proposes, for the first time, two efficient parallel implementations of the exact Sorting-based Nearest Ne...
Direct sensor–digital device interfaces measure time dependent variables of simple circuits to implement analog-to-digital conversion. Field Programmable Gate Arrays (FPGAs) are devices whose hardware can be reconfigured to work in parallel. They usu...
To optimize the efficiency of the geospatial service in the flood response decision making system, a Parallel Agent-as-a-Service (P-AaaS) method is proposed and implemented in the cloud. The prototype system and comparisons demonstrate the advantages...
This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper descr...
P system is a computing model that imitates a natural process that occurs at a cellular level where all objects evolve in a maximal parallelism and distributed manner. Recent results show that it could be used to solve some problems for less computat...
The system performances can be potentially enhanced for three-phase inverter parallel operation in droop-controlled AC microgrid by using network-based control, which also benefits for the extension of other control strategies in microgrids (MGs). It...
Geospatial transformations in the form of reprojection calculations for large datasets can be computationally intensive; as such, finding better, less expensive ways of achieving these computations is desired. In this paper, we report our efforts in...
Recently, numerous graph partitioning approaches have been proposed to distribute a big graph to machines in a cluster for distributed computing. Due to heavy communication overhead, these graph partitioning approaches always suffered from long ingre...
Estimating the state of health of lithium-ion batteries in energy storage systems is a key step in their subsequent safety monitoring and energy optimization management. This study proposes a method for estimating the state of health of lithium-ion b...
This article investigates the efficiency of a doParallel algorithm and a formal concept analysis (FCA) network graph applied to recommendation systems. It is the first article using the FCA method to create a network graph and apply this graph to imp...
It is challenging to build a real-time information retrieval system, especially for systems with high-dimensional big data. To structure big data, many hashing algorithms that map similar data items to the same bucket to advance the search have been...
Digital image compression is applied to reduce camera bandwidth and storage requirements, but real-time lossless compression on a high-speed high-resolution camera is a challenging task. The article presents hardware implementation of a Bayer colour...
Accurate Remaining Useful Life (RUL) prediction of lithium batteries is crucial for enhancing their performance and extending their lifespan. Existing studies focus on continuous or relatively sparse datasets; however, continuous and complete dataset...
Thread-level and data-level parallel architectures have become the design of choice in many of today’s energy-efficient computing systems. However, these architectures put substantially higher requirements on the memory subsystem than scalar architec...
The financial data supply chain is vital to the economy, especially for banks. It affects their customer service level, therefore, it is crucial to manage the scheduling of the financial data supply chain to elevate the efficiency of banking sectors’...
Arable land quality (ALQ) data are a foundational resource for national food security. With the rapid development of spatial information technologies, the annual acquisition and update of ALQ data covering the country have become more accurate and fa...
The visualization of geographic vector data is an important premise for spatial analysis and spatial cognition. Traditional geographic vector data visualization methods are data-driven, and their computational costs have increased rapidly with the gr...
In practice, single item support cannot comprehensively address the complexity of items in large datasets. In this study, we propose a big data analytics framework (named Multiple Item Support Frequent Patterns, MISFP-growth algorithm) that uses Hado...
Maintenance and repair play a crucial role in industry. Smart systems for technical diagnostics can help to save money and to prevent the breakdown of machines and plants. These systems and its classifiers benefit from plausible features because they...
In this paper, a spatial two-degree-of-freedom (2DOF) parallel platform based on electromagnetic redundant drive and its control method are investigated. The platform is redundantly driven by three electromagnetic-spring conforming branched chains, a...
Vast amounts of data are continuously collected through sensors fitted into various pieces of equipment and processes in semiconductor production lines. These integrated datasets often encompass tens of thousands of dimensions, making it challenging...
Multiple object tracking is used in a range of applications, including autonomous control of various vehicles and sports analytics. The main challenges in developing tracking systems are detection errors and computational load that scales with the nu...
In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS)...
of 140