2023 March - 51 articles
Although current computer vision systems are closer to the human intelligence when it comes to comprehending the visible world than previously, their performance is hindered when objects are partially occluded. Since we live in a dynamic and complex...
Automatic recommendation systems based on deep neural networks have become extremely popular during the last decade. Some of these systems can, however, be used in applications that are ranked as High Risk by the European Commission in the AI act&mda...
Practitioners have used hidden Markov models (HMMs) in different problems for about sixty years. Moreover, conditional random fields (CRFs) are an alternative to HMMs and appear in the literature as different and somewhat concurrent models. We propos...
In this study, we tackle a key scheduling problem in a robotic arm-based food processing system, where multiple conveyors—an infeed conveyor that feeds food items to robotic arms and two tray lane conveyors, on which trays to batch food items a...
3D mesh as a complex data structure can provide effective shape representation for 3D objects, but due to the irregularity and disorder of the mesh data, it is difficult for convolutional neural networks to be directly applied to 3D mesh data process...
This paper proposes a new data structure, multiset-trie, that is designed for storing and efficiently processing a set of multisets. Moreover, multiset-trie can operate on a set of sets without efficiency loss. The multiset-trie structure is a search...
Incremental techniques aim at making it possible to improve the performance of the grounding and solving processes by reusing the results of previous executions. Clingo supports both incremental grounding and incremental solving computations. In orde...
Animal models of diseases, particularly mice, are considered to be the cornerstone for translational research in immunology. The aim of the present study is to model the geometry and analyze the network structure of the murine lymphatic system (LS)....
The efficiency and the effectiveness of a machine learning (ML) model are greatly influenced by feature selection (FS), a crucial preprocessing step in machine learning that seeks out the ideal set of characteristics with the maximum accuracy possibl...
Acute myeloid leukemia (AML) is a type of blood cancer that affects both adults and children. Benzene exposure has been reported to increase the risk of developing AML in children. The assessment of the potential relationship between environmental be...
Artificial intelligence systems are increasingly being used in industrial applications, security and military contexts, disaster response complexes, policing and justice practices, finance, and healthcare systems. However, disruptions to these system...
Roundabout design is an iterative process consisting of a preliminary geometry design, geometry performance checks, and the estimation of intersection functionality (based on the results of analytical or regression models). Since both roundabout geom...
In this manuscript, we carry out a study on the generalization of a known family of multipoint scalar iterative processes for approximating the solutions of nonlinear systems. The convergence analysis of the proposed class under various smooth condit...
The Shortest Path (SP) problem resembles a variety of real-world situations where one needs to find paths between origins and destinations. A generalization of the SP is the Dynamic Shortest Path (DSP) problem, which also models changes in the graph...
Accurate sizing systems of a population permit the minimization of the production costs of the textile apparel industry and allow firms to satisfy their customers. Hence, information about human body shapes needs to be extracted in order to examine,...
QR codes (short for Quick Response codes) were originally developed for use in the automotive industry to track factory inventories and logistics, but their popularity has expanded significantly in the past few years due to the widespread application...
In the last few years, we have witnessed the spread of computing devices getting smaller and smaller (e.g., Smartphones, Smart Devices, Raspberry, etc.), and the production and availability of data getting bigger and bigger. This work presents DLV-EE...
Instructors face significant time and effort constraints when grading students’ assessments on a large scale. Clustering similar assessments is a unique and effective technique that has the potential to significantly reduce the workload of inst...
Cryptographic S-boxes are vectorial Boolean functions that must fulfill strict criteria to provide security for cryptographic algorithms. There are several existing methods for generating strong cryptographic S-boxes, including stochastic search algo...
In this paper, we present a new third-order family of iterative methods in order to compute the multiple roots of nonlinear equations when the multiplicity
The widespread adoption of advanced technologies, such as Artificial Intelligence (AI), Machine Learning, and Robotics, is rapidly increasing across the globe. This accelerated pace of change is drastically transforming various aspects of our lives a...
Crowd congestion is one of the main causes of modern public safety issues such as stampedes. Conventional crowd congestion monitoring using closed-circuit television (CCTV) video surveillance relies on manual observation, which is tedious and often e...
Because of the acoustic characteristics of bone-conducted (BC) speech, BC speech can be enhanced to better communicate in a complex environment with high noise. Existing BC speech enhancement models have weak spectral recovery capability for the high...
Anomaly detection is one of the basic issues in data processing that addresses different problems in healthcare sensory data. Technology has made it easier to collect large and highly variant time series data; however, complex predictive analysis mod...
Human resource management has a significant influence on the performance of any public body. Employee classification and ranking are definitely time-consuming processes, which in many cases lead to controversial results. In addition, assessing employ...
In this work, the quantum random walk search algorithm with a walk coin constructed by generalized Householder reflection and phase multiplier has been studied. The coin register is one qudit with an arbitrary dimension. Monte Carlo simulations, in c...
Surface electromyography (sEMG) plays a crucial role in several applications, such as for prosthetic controls, human–machine interfaces (HMI), rehabilitation, and disease diagnosis. These applications are usually occurring in real-time, so the...
We investigate a solution of a convex programming problem with a strongly convex objective function based on the dual approach. A dual optimization problem has constraints on the positivity of variables. We study the methods and properties of transfo...
Hemorrhages in the retinal fundus are a common symptom of both diabetic retinopathy and diabetic macular edema, making their detection crucial for early diagnosis and treatment. For this task, the aim is to evaluate the performance of two pre-trained...
Artificial intelligence and machine learning (AI/ML) research has aimed to achieve human-level performance in tasks that require understanding and decision making. Although major advances have been made, AI systems still struggle to achieve adaptive...
Supervised and unsupervised classification algorithms are the two main branches of machine learning [...]
In parameterized complexity, it is well-known that a parameterized problem is fixed-parameter tractable if and only if it has a kernel—an instance equivalent to the input instance, whose size is just a function of the parameter. The size of the...
Graphs are versatile structures for the representation of many real-world data. Deep Learning on graphs is currently able to solve a wide range of problems with excellent results. However, both the generation of graphs and the handling of large graph...
In this paper, we describe a model for the automatic generation of literary sentences in French. Although there has been much recent effort directed towards automatic text generation in general, the generation of creative, literary sentences that is...
Wearable devices used for personal monitoring applications have been improved over the last decades. However, these devices are limited in terms of size, processing capability and power consumption. This paper proposes an efficient hardware/software...
The impact of COVID-19 and the pressure it exerts on health systems worldwide motivated this study, which focuses on the case of Greece. We aim to assist decision makers as well as health professionals, by estimating the short to medium term needs in...
We propose a way of dealing with invasive species or pest control in agriculture. Ecosystems can be modeled via dynamical systems. For their study, it is necessary to establish their possible equilibria. Even a moderately complex system exhibits, in...
This paper proposes an interconnection of the MATLAB and GAMS software interfaces, which were designed based on a master-slave methodology, to solve the mixed-integer nonlinear programming (MINLP) model problem associated with the problem regarding t...
This paper presents an echo suppression system that combines a linear acoustic echo canceller (AEC) with a deep complex convolutional recurrent network (DCCRN) for residual echo suppression. The filter taps of the AEC are adjusted in subbands by usin...
Digitization and transcription of historic documents offer new research opportunities for humanists and are the topics of many edition projects. However, manual work is still required for the main phases of layout recognition and the subsequent optic...
This article introduces a novel nature-inspired algorithm called the Plum Tree Algorithm (PTA), which has the biology of the plum trees as its main source of inspiration. The PTA was tested and validated using 24 benchmark objective functions, and it...
In our digital age, data are generated constantly from public and private sources, social media platforms, and the Internet of Things. A significant portion of this information comes in the form of unstructured images and videos, such as the 95 milli...
Differential evolution (DE) is a popular and efficient heuristic numerical optimization algorithm that has found many applications in various fields. One of the main disadvantages of DE is its sensitivity to parameter values. In this study, we invest...
Many highly contagious infectious diseases, such as COVID-19, monkeypox, chickenpox, influenza, etc., have seriously affected or currently are seriously affecting human health, economic activities, education, sports, and leisure. Many people will be...
The Gromov-Wasserstein (GW) formalism can be seen as a generalization of the optimal transport (OT) formalism for comparing two distributions associated with different metric spaces. It is a quadratic optimization problem and solving it usually has c...
Affective computing focuses on instilling emotion awareness in machines. This area has attracted many researchers globally. However, the lack of an affective database based on physiological signals from the Asian continent has been reported. This is...
The purpose of a circle packing procedure is to fill up a predefined, geometrical, closed contour with a maximum finite number of circles. The subject has received considerable attention in pure and applied sciences and has proved to be highly effect...
The adoption of deep neural networks for profiling side-channel attacks opened new perspectives for leakage detection. Recent publications showed that cryptographic implementations featuring different countermeasures could be broken without feature s...
The bi-dimensional F1-Transform was applied in image analysis to improve the performances of the F-transform method; however, due to its high computational complexity, the multidimensional F1-transform cannot be used in data analysis problems, especi...
In recent years, graph neural networks (GNNs) have played an important role in graph representation learning and have successfully achieved excellent results in semi-supervised classification. However, these GNNs often neglect the global smoothing of...
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