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...
Recently, as the amount of real-time video streaming data has increased, distributed parallel processing systems have rapidly evolved to process large-scale data. In addition, with an increase in the scale of computing resources constituting the dist...
Distributed stream processing engines (DSPEs) deploy multiple tasks on distributed servers to process data streams in real time. Many DSPEs have provided locality-aware stream partitioning (LSP) methods to reduce network communication costs. However,...
With the upswing in the volume of data, information online, and magnanimous cloud applications, big data analytics becomes mainstream in the research communities in the industry as well as in the scholarly world. This prompted the emergence and devel...
The location-based aggregate queries, consisting of the shortest average distance query (SAvgDQ), the shortest minimal distance query (SMinDQ), the shortest maximal distance query (SMaxDQ), and the shortest sum distance query (SSumDQ) are new types o...
Recently, there has been an explosive generation of streaming data in various fields such as IoT and network attack detection, medical data monitoring, and financial trend analysis. These domains require precise and rapid analysis capabilities by min...
The computational complexity of the multiple-input and multiple-output (MIMO) based least square algorithm is very high and it cannot be run on processing-inefficient low-cost platforms. To overcome complexity-related problems, a parallel distributed...
Efficient distributed processing is vital for collaborative searching tasks of robotic swarm systems. Typically, those systems are decentralized, and the members have only limited communication and processing capacities. What is illustrated in this p...
Various distributed processing schemes were studied to efficiently utilize a large scale of RDF graph in semantic web services. This paper proposes a new distributed SPARQL query processing scheme considering communication costs in Spark environments...
Stream processing frameworks have become key enablers of real-time data processing in modern distributed systems. However, robust and scalable mechanisms for verifying temporal properties are often lacking in existing systems. To address this gap, a...
Because of their high spatial resolution over extended lengths, distributed fiber optic sensors (DFOS) enable us to monitor a wide range of structural effects and offer great potential for diverse structural health monitoring (SHM) applications. Howe...
Big Data and primarily distributed stream processing systems (DSPSs) are growing in complexity and scale. As a result, effective performance management to ensure that these systems meet the required service level objectives (SLOs) is becoming increas...
A growing number of services and applications are developed using multimedia sensing low-cost wireless devices, thus creating the Internet of Multimedia Things (IoMT). Nevertheless, energy efficiency and resource availability are two of the most chal...
The magnitude of highly dynamic spatial data is expanding rapidly due to the instantaneous evolution of mobile technology, resulting in challenges for continuous queries. We propose a novel indexing approach model, namely, the Velocity SpatioTemporal...
Remote sensing of the atmospheric composition from current and future satellites, such as the Sentinel missions of the Copernicus programme, yields an unprecedented amount of data to monitor air quality, ozone, UV radiation and other climate variable...
Data stream partitioning is a fundamental and important mechanism for distributed systems. However, use of an inappropriate partition scheme may generate a data skew problem, which can influence the execution efficiency of many application tasks. Pro...
The availability of geodata with high spatial and temporal resolution is increasing steadily. Often, these data are continuously generated by distributed sensor networks and provided as geodata streams. Geostatistical analysis methods, such as spatio...
With accelerating urbanization and the exponential growth in vehicle populations, high-precision traffic monitoring has become indispensable for intelligent transportation systems (ITSs). Conventional sensing technologies—including inductive lo...
This paper demonstrates how the processing of Brillouin gain spectra (BGS) by two-dimensional correlation methods improves the accuracy of Brillouin frequency shift (BFS) extraction in distributed fiber optic sensor systems based on the BOTDA/BOTDR (...
Uncertainty in processing times is a key issue in distributed production; it severely affects scheduling accuracy. In this study, we investigate a dynamic distributed flexible job shop scheduling problem with variable processing times (DDFJSP-VPT), i...
A common approach to simulating a Lévy process is to truncate its shot-noise representation. We focus on subordinators and introduce the remainder process, which represents the jumps that are removed by the truncation. We characterize when the...
The increase of Internet of Things devices and the rise of more computationally intense applications presents challenges for future Internet of Things architectures. We envision a future in which edge, fog, and cloud devices work together to execute...
In real life, indeterminacy and determinacy are symmetric, while indeterminacy is absolute. We are devoted to studying indeterminacy through uncertainty theory. Within the framework of uncertainty theory, uncertain processes are used to model the evo...
In this study, a renewal reward process with a discrete interference of chance (X(t)) is constructed and distribution of the process X(t) is investigated. One dimensional distribution of the process X(t) is given by means of the probability characte...
An infinite sequence x 1 x 2 …...
Discrete-valued time series modeling has witnessed numerous bivariate first-order integer-valued autoregressive process or BINAR(1) processes based on binomial thinning and different innovation distributions. These BINAR(1) processes are mainly focus...
The control of arsenic, a toxic and carcinogenic element, is an important issue for all copper smelters. In this work, the reaction mechanism and distribution behavior of arsenic in the bottom blown copper smelting process (SKS process) were investig...
Two-process surfaces are functionally important. They contain plateau and valley parts. They are created by superimpositions of two one-process textures of Gaussian probability height distributions. It is expected that the resulting two-process surfa...
This paper considers trajectory a modeling problem for a multi-agent system by using the Gaussian processes. The Gaussian process, as the typical data-driven method, is well suited to characterize the model uncertainties and perturbations in a comple...
The increase in the number of devices equipped with physiological sensors and their low price mean that they can be used in many fields. One of these fields is health-care and home-care for the elderly or people with disabilities. The development of...
The significance of count data modeling and its applications to real-world phenomena have been highlighted in several research studies. The present study focuses on a two-parameter discrete distribution that can be obtained by compounding the Poisson...
The process performance index (PPI) can be a simple metric to connect the conforming rate of products. The properties of the PPI have been well studied for the normal distribution and other widely used lifetime distributions, such as the Weibull, Gam...
Organizations in the agroindustry sector face shorter delivery schedules; therefore, they are seeking ways to conduct more effective and less costly product distribution. Supply chain management efforts have focused on improving the flow of both prod...
This study investigates sediment transport processes in the Kelani River Basin, Sri Lanka, focusing on the formation of bed material sediment size distributions. Sediment transport processes during the flood events in 2016 and 2018 are evaluated usin...
The control of tension in processing lines for metal strips tackles several problems. The process of achieving high tension driven by a multi-motor drive system, where the motors are mechanically coupled by a strip, is affected by the maximal torque...
With increasing impurity contents in concentrates, the control of the minor elements is an important issue for the oxygen bottom blown copper smelting process (Shuikoushan process or SKS process). In this work, the distribution behaviors of the minor...
As various services have been generating large-scale graphs to represent multiple relationships between objects, studies have been conducted to obtain subgraphs with particular patterns. In this paper, we propose a distributed query processing method...
The entropy evaluation method of assembly stress has become a hot topic in recent years. However, the current research can only evaluate the maximum stress magnitude and stress magnitude uniformity, and it cannot evaluate the stress position distribu...
Forest road aggregate changes due to traffic. The physical processes that cause these aggregate changes need to be understood for more effective road management that can help reduce maintenance costs and efforts, and negative environmental impacts of...
The use of distribution-based data representation to handle large-scale scientific datasets is a promising approach. Distribution-based approaches often transform a scientific dataset into many distributions, each of which is calculated from a small...
The Generalized Renewal Process (GRP) is a probabilistic model for repairable systems that can represent the usual states of a system after a repair: as new, as old, or in a condition between new and old. It is often coupled with the Weibull distribu...
Due to the diversity and complexity of distribution networks, the classical modular software development method may face the difficulty in modular division, data sharing and collaboration of different specialties. Inspired by the idea of separating t...
Surface composite fabrication through Friction Stir Processing (FSP) is evolving as a useful clean process to enhance surface properties of substrate. Better particle distribution is key to the success of surface composite fabrication which is achiev...
Stochastic processes are useful and important for modeling the evolution of processes that take different states over time, a situation frequently found in fields such as medical research and engineering. In a previous paper and within this framework...
(1) Background: The literature discusses the inverse Maxwell distribution theoretically without application. Control charting is promising, but needs development for inverse Maxwell processes. (2) Methods: Thus, we develop the VIM control chart for m...
Quantum key distribution (QKD) has been researched for almost four decades and is currently making its way to commercial applications. However, deployment of the technology at scale is challenging because of the very particular nature of QKD and its...
In this study, the grain boundary character distribution (GBCD) of a B10 alloy was optimized, employing thermomechanical processing consisting of friction stirring processing (FSP) and annealing treatment. Using electron backscatter diffraction, the...
This paper provides a comprehensive and systematic review of fault diagnosis methods based on artificial intelligence (AI) in smart distribution networks described in the literature. For the first time, it systematically combs through the main fault...
With the increasing concern for the environment, energy-efficient scheduling of the manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time affect the final energy consumption and thus the s...
Two Rényi-type generalizations of the Shannon cross-entropy, the Rényi cross-entropy and the Natural Rényi cross-entropy, were recently used as loss functions for the improved design of deep learning generative adversarial networ...
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