October 2022 - 56 articles
Most machine-learning algorithms assume that instances are independent of each other. This does not hold for networked data. Node representation learning (NRL) aims to learn low-dimensional vectors to represent nodes in a network, such that all actio...
The main purpose of mathematical model building while employing statistical data analysis is to obtain high accuracy of approximation within the range of observed data and sufficient predictive properties. One of the methods for creating mathematical...
The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution, and sched...
In recent years, studying and predicting mobility patterns in urban environments has become increasingly important as accurate and timely information on current and future vehicle flows can successfully increase the quality and availability of transp...
Cyclic scheduling is of vital importance in a repetitive discrete manufacturing environment. We investigate scheduling in the context of general cyclic job shops with blocking where there are no intermediate buffers between the machines. We also cons...
A bilateral filter is a non-linear denoising algorithm that can reduce noise while preserving the edges. This study explores the characteristics of a bilateral filter in changing the noise and texture within computed tomography (CT) images in an iter...
Background: The technological revolution has allowed users to exchange data and information in various fields, and this is one of the most prevalent uses of computer technologies. However, in a world where third parties are capable of collecting, ste...
In this research, we present a hybrid algorithmic framework and its integration into the precise production scheduling system of a Greek metal forming factory. The system was created as a decision support tool to assist production planners in arrangi...
The absence of a conventional association between the cell–cell cohabitation and its emergent dynamics into cliques during development has hindered our understanding of how cell populations proliferate, differentiate, and compete (i.e., the cel...
Automated deep learning and data mining algorithms can provide accurate detection, frequency patterns, and predictions of dangerous goods passing through motorways and tunnels. This paper presents a post-processing image detection application and a t...
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