2020 December - 39 articles
This work uses the sliding mode control method to conduct the finite-time synchronization of chaotic systems. The utilized parameter selection principle differs from conventional methods. The designed controller selects the unknown parameters indepen...
Text clustering is one of the efficient unsupervised learning techniques used to partition a huge number of text documents into a subset of clusters. In which, each cluster contains similar documents and the clusters contain dissimilar text documents...
Langton’s ant is a deterministic cellular automaton studied in many fields, artificial life, computational complexity, cryptography, emergent dynamics, Lorents lattice gas, and so forth, motivated by the hardness of predicting the ant’s m...
Solving the person re-identification problem involves making associations between the same person’s appearances across disjoint camera views. Further, those associations have to be made on multiple surveillance cameras in order to obtain a more...
To manage multidimensional point data more efficiently, this paper presents an improvement, called HD-tree, of a previous indexing method, called D-tree. Both structures combine quadtree-like partitioning (using integer shift operations without stori...
We implement and test the performances of several approximation algorithms for computing the minimum dominating set of a graph. These algorithms are the standard greedy algorithm, the recent Linear programming (LP) rounding algorithms and a hybrid al...
In recent years, there have been several attempts to use machine learning techniques to improve the performance of exact and approximate optimization algorithms. Along this line of research, the present paper shows how supervised and unsupervised tec...
Recently, very large-scale decision support systems (DSSs) have been developed, which tackle very complex problems, associated with very extensive and polymorphic information, which probably is geographically highly dispersed. The management, updatin...
With the development of E-commerce, online advertising began to thrive and has gradually developed into a new mode of business, of which Click-Through Rates (CTR) prediction is the essential driving technology. Given a user, commodities and scenarios...
Evaluation of agricultural investment climate has essential reference value for site selection, operation and risk management of agricultural outward foreign direct investment projects. This study builds a back propagation neural network-based agric...
Project Planning and Control (PPC) problems with stochastic job processing times belong to the problem class of Stochastic Resource-Constrained Multi-Project Scheduling Problems (SRCMPSP). A practical example of this problem class is the industrial d...
In railway traffic systems, whenever disturbances occur, it is important to effectively reschedule trains while optimizing the goals of various stakeholders. Algorithms can provide significant benefits to support the traffic controllers in train resc...
The Guidance, Navigation and Control (GNC) of air and space vehicles has been one of the spearheads of research in the aerospace field in recent times. Using Global Navigation Satellite Systems (GNSS) and inertial navigation systems, accuracy may be...
Methods of topological data analysis have been successfully applied in a wide range of fields to provide useful summaries of the structure of complex data sets in terms of topological descriptors, such as persistence diagrams. While there are many po...
Lyme disease is a rapidly growing illness that remains poorly understood within the medical community. Critical questions about when and why patients respond to treatment or stay ill, what kinds of treatments are effective, and even how to properly d...
Understanding the behaviors and intentions of humans is still one of the main challenges for vehicle autonomy. More specifically, inferring the intentions and actions of vulnerable actors, namely pedestrians, in complex situations such as urban traff...
Hyperspectral image classification has been increasingly used in the field of remote sensing. In this study, a new clustering framework for large-scale hyperspectral image (HSI) classification is proposed. The proposed four-step classification scheme...
Incomplete data are a common feature in many domains, from clinical trials to industrial applications. Bayesian networks (BNs) are often used in these domains because of their graphical and causal interpretations. BN parameter learning from incomplet...
In the paper we deal with the problem of non-linear dynamic system identification in the presence of random noise. The class of considered systems is relatively general, in the sense that it is not limited to block-oriented structures such as Hammers...
Bayesian inference using Gaussian processes on large datasets have been studied extensively over the past few years. However, little attention has been given on how to apply these on a high resolution input space. By approximating the set of test poi...
In 2020 Dombi and Jónás (Acta Polytechnica Hungarica 17:1, 2020) introduced a new four parameter probability distribution which they named the pliant probability distribution family. One of the special members of this family is the so-c...
Currently, input modeling for Monte Carlo simulation (MSC) is performed either by fitting a probability distribution to historical data or using expert elicitation methods when historical data are limited. These approaches, however, are not suitable...
The general assignment problem is a classical NP-hard (non-deterministic polynomial-time) problem. In a warehouse, the constraints on the equipment and the characteristics of consecutive processes make it even more complicated. To overcome the diffic...
Generative models for images, audio, text, and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods fo...
In the field of image processing, there are several difficult issues that do not have exact solutions due to incomplete or imperfect information and limited computation capacity [...]
In a previous paper we defined the black and white SAT problem which has exactly two solutions, where each variable is either true or false. We showed that black and white 2-SAT problems represent strongly connected directed graphs. We presented also...
An epidemic model, the so-called SE(Is)(Ih)(Iicu)AR epidemic model, is proposed which splits the infectious subpopulation of the classical SEIR (Susceptible-Exposed-Infectious-Recovered) model into four subpopulations, namely asymptomatic infectious...
This work addresses the problem of using Unmanned Aerial Vehicles (UAV) to deploy a wireless aerial relay communications infrastructure for stations scattered on the ground. In our problem, every station in the network must be assigned to a single UA...
Conventionally, the similarity between two images is measured by the easy-calculating Euclidean distance between their corresponding image feature representations for image retrieval. However, this kind of direct similarity measurement ignores the lo...
The focus of present research endeavor was to design a robust fractional-order proportional-integral-derivative (FOPID) controller with specified phase margin (PM) and gain cross over frequency (
Simple and easy to use methods are of great practical demand in the design of Proportional, Integral, and Derivative (PID) controllers. Controller design criteria are to achieve a good set-point tracking and disturbance rejection with minimal actuato...
Creating simplified visualizations of large 3D trail sets with limited occlusion and preservation of the main structures in the data is challenging. We address this challenge for the specific context of 3D fiber trails created by DTI tractography. Fo...
The goal of full-reference image quality assessment (FR-IQA) is to predict the perceptual quality of an image as perceived by human observers using its pristine (distortion free) reference counterpart. In this study, we explore a novel, combined appr...
The ancestral mixture model, an important model building a hierarchical tree from high dimensional binary sequences, was proposed by Chen and Lindsay in 2006. As a phylogenetic tree (or evolutionary tree), a mixture tree created from ancestral mixtur...
The k-means problem is to compute a set of k centers (points) that minimizes the sum of squared distances to a given set of n points in a metric space. Arguably, the most common algorithm to solve it is k-means++ which is easy to implement and provid...
A completely new economic system is required for the era of Industry 4.0. Blockchain technology and blockchain cryptocurrencies are the best means to confront this new trustless economy. Millions of smart devices are able to complete transparent fina...
Due to the availability of Industry 4.0 technology, the application of big data analytics to automated systems is possible. The distribution of products between warehouses or within a warehouse is an area that can benefit from automation based on Ind...
Irregular shape clustering is always a difficult problem in clustering analysis. In this paper, by analyzing the advantages and disadvantages of existing clustering analysis algorithms, a new neighborhood density correlation clustering (NDCC) algorit...
Sign Languages (SLs) are visual–gestural languages that have developed naturally in deaf communities. They are based on the use of lexical signs, that is, conventionalized units, as well as highly iconic structures, i.e., when the form of an ut...
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