Feature Papers in Algorithms

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Faculty of Mathematics, Otto-von-Guericke-University, P.O. Box 4120, D-39016 Magdeburg, Germany
Interests: scheduling, in particular development of exact and approximate algorithms; stability investigations is discrete optimization; scheduling with interval processing times; complexity investigations for scheduling problems; train scheduling; graph theory; logistics; supply chains; packing; simulation and applications
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This is a collection of top-quality papers published in open-access form by those invited by the editorial office and the Editor-in-Chief. Papers could be both long research papers and papers describing the current state of the art in one of the areas covered by the journal.

Prof. Dr. Frank Werner
Collection Editor

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Published Papers (23 papers)

2024

Jump to: 2023, 2022

38 pages, 2189 KiB  
Review
Algorethics in Healthcare: Balancing Innovation and Integrity in AI Development
by Andrea Lastrucci, Antonia Pirrera, Graziano Lepri and Daniele Giansanti
Algorithms 2024, 17(10), 432; https://doi.org/10.3390/a17100432 - 27 Sep 2024
Viewed by 444
Abstract
The rapid advancement of artificial intelligence (AI) technology has catalyzed unprecedented innovation in the healthcare industry, transforming medical practices and patient care. However, this progress brings significant ethical challenges, highlighting the need for a comprehensive exploration of algorethics—the intersection of algorithm design and [...] Read more.
The rapid advancement of artificial intelligence (AI) technology has catalyzed unprecedented innovation in the healthcare industry, transforming medical practices and patient care. However, this progress brings significant ethical challenges, highlighting the need for a comprehensive exploration of algorethics—the intersection of algorithm design and ethical considerations. This study aimed to conduct a narrative review of reviews in the field of algorethics with specific key questions. The review utilized a standardized checklist for narrative reviews, including the ANDJ Narrative Checklist, to ensure thoroughness and consistency. Searches were performed on PubMed, Scopus, and Google Scholar. The review revealed a growing emphasis on integrating fairness, transparency, and accountability into AI systems, alongside significant progress in ethical AI development. The importance of collaboration between different domains of scientific production, such as social sciences and standardization (like the IEEE), and the development of guidelines is significantly emphasized, with demonstrated direct impact in the health domain. However, gaps persist, particularly in the lack of standardized evaluation methods and the challenges posed by complex sectors like healthcare. The findings underscore the need and importance for robust data governance to prevent biases and highlight the importance of cross-disciplinary collaboration in creating comprehensive ethical frameworks for AI. The field of algorethics has important applications in the health domain, and there is a significant increase in attention, with a focus on addressing issues and seeking both practical and theoretical solutions. Future research should prioritize establishing standardized evaluation practices for AI, fostering interdisciplinary collaboration, developing sector-specific ethical guidelines, exploring AI’s long-term societal impacts, and enhancing ethical training for developers. Continued attention to emerging ethical standards is also crucial for aligning AI technologies with evolving ethical principles. Full article
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24 pages, 4557 KiB  
Article
A System Design Perspective for Business Growth in a Crowdsourced Data Labeling Practice
by Vahid Hajipour, Sajjad Jalali, Francisco Javier Santos-Arteaga, Samira Vazifeh Noshafagh and Debora Di Caprio
Algorithms 2024, 17(8), 357; https://doi.org/10.3390/a17080357 - 15 Aug 2024
Viewed by 357
Abstract
Data labeling systems are designed to facilitate the training and validation of machine learning algorithms under the umbrella of crowdsourcing practices. The current paper presents a novel approach for designing a customized data labeling system, emphasizing two key aspects: an innovative payment mechanism [...] Read more.
Data labeling systems are designed to facilitate the training and validation of machine learning algorithms under the umbrella of crowdsourcing practices. The current paper presents a novel approach for designing a customized data labeling system, emphasizing two key aspects: an innovative payment mechanism for users and an efficient configuration of output results. The main problem addressed is the labeling of datasets where golden items are utilized to verify user performance and assure the quality of the annotated outputs. Our proposed payment mechanism is enhanced through a modified skip-based golden-oriented function that balances user penalties and prevents spam activities. Additionally, we introduce a comprehensive reporting framework to measure aggregated results and accuracy levels, ensuring the reliability of the labeling output. Our findings indicate that the proposed solutions are pivotal in incentivizing user participation, thereby reinforcing the applicability and profitability of newly launched labeling systems. Full article
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2023

Jump to: 2024, 2022

16 pages, 6941 KiB  
Article
An Alternative Multi-Physics-Based Methodology for Strongly Coupled Electro-Magneto-Mechanical Problems
by Federico Maria Reato, Claudio Ricci, Jan Misfatto, Matteo Calzaferri and Simone Cinquemani
Algorithms 2023, 16(6), 306; https://doi.org/10.3390/a16060306 - 19 Jun 2023
Viewed by 1356
Abstract
The analysis of complex systems tends to be approached through a separation and a simplification of the main macro phenomena and, thus, addressed through dedicated techniques, tools, and algorithms. A smart and interesting possibility, instead, is represented by the so-called model-based design analysis, [...] Read more.
The analysis of complex systems tends to be approached through a separation and a simplification of the main macro phenomena and, thus, addressed through dedicated techniques, tools, and algorithms. A smart and interesting possibility, instead, is represented by the so-called model-based design analysis, which allows one to interface phenomena coming from interactions of different physical natures. This paper aims to propose a multi-physics Matlab/Simulink®-based architecture that allows one to integrate general and strongly non-linear coupling phenomena, taking efforts from two novel implemented bi-directional co-simulation routines based on Spice® and ESRF Radia® engines. Emphasis is dedicated to the discussion and description of the co-simulation algorithms and processes characteristic of these routines, which allow the analog electronic and the magneto dynamic domain’s integration under a single simulation environment. To highlight the reliability of the multi-domain architecture and to validate the reported co-simulation results, a comparison with the experimental measures obtained on an innovative MEMS electromagnetic actuator are proposed. Full article
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14 pages, 4156 KiB  
Article
Identification of Highlighted Cells in Low-Variance Raster Data Application to Digital Elevation Models
by Manuel Antonio Ureña-Cámara and Antonio Tomás Mozas-Calvache
Algorithms 2023, 16(6), 302; https://doi.org/10.3390/a16060302 - 16 Jun 2023
Cited by 1 | Viewed by 1187
Abstract
This study describes a new algorithm developed to detect local cells of minimum or maximum heights in grid Digital Elevation Models (DEMs). DEMs have a low variance in digital levels due to the spatial continuity of the data. Traditional algorithms, such as SIFT, [...] Read more.
This study describes a new algorithm developed to detect local cells of minimum or maximum heights in grid Digital Elevation Models (DEMs). DEMs have a low variance in digital levels due to the spatial continuity of the data. Traditional algorithms, such as SIFT, are based on statistical variance, which present issues to determine these highlighted cells. However, one of the main purposes of this identification is the use of these points (cells) to assess the positional accuracy of these products by comparing those extracted from the DEM with those obtained from a more accurate source. In this sense, we developed an algorithm based on a moveable window composed of variable sizes, which is displaced along the image to characterize each set of cells. The determination of highlighted cells is based on the absolute differences of digital levels in the same DEM and compared to those obtained from other DEMs. The application has been carried out using a great number of data, considering four zones, two spatial resolutions, and different definitions of height surfaces. The results have demonstrated the feasibility of the algorithm for the identification of these cells. Thus, this approach expects an improvement in traditional procedures. The algorithm can be used to contrast DEMs obtained from different sources or DEMs from the same source that have been affected by generalization procedures. Full article
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13 pages, 958 KiB  
Communication
On a Class of Orthogonal Polynomials as Corrections in Lienard Differential System: Applications
by Vesselin Kyurkchiev, Anton Iliev, Asen Rahnev and Nikolay Kyurkchiev
Algorithms 2023, 16(6), 297; https://doi.org/10.3390/a16060297 - 12 Jun 2023
Cited by 12 | Viewed by 1341
Abstract
In this paper we demonstrate some specialized modules for investigating the dynamics of differential models, an integral part of a planned much more general Web-based application for scientific computing. As “corrections” in the Lienard differential system is presented a class of orthogonal polynomials [...] Read more.
In this paper we demonstrate some specialized modules for investigating the dynamics of differential models, an integral part of a planned much more general Web-based application for scientific computing. As “corrections” in the Lienard differential system is presented a class of orthogonal polynomials (also known as “shell polynomials”). We will note that some specifics of the amplitudes of these polynomials open up the possibility of modeling signals from the field of antenna-feeder techniques. Algorithms and modules have been consistently used for: automatic generation of a theorem on the number and type of limit cycles (in the light of Melnikov’s considerations); study of the Hamiltonian of the system and “level curves”; for the study of catastrophic surfaces (in the light of Zeeman’s considerations), etc. Similar studies have been carried out for associated polynomials. Numerical examples, illustrating our results using CAS MATHEMATICA are given. Full article
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25 pages, 8154 KiB  
Article
A Fast Hybrid Pressure-Correction Algorithm for Simulating Incompressible Flows by Projection Methods
by Jiannong Fang
Algorithms 2023, 16(6), 287; https://doi.org/10.3390/a16060287 - 2 Jun 2023
Viewed by 1737
Abstract
To enforce the conservation of mass principle, a pressure Poisson equation arises in the numerical solution of incompressible fluid flow using the pressure-based segregated algorithms such as projection methods. For unsteady flows, the pressure Poisson equation is solved at each time step usually [...] Read more.
To enforce the conservation of mass principle, a pressure Poisson equation arises in the numerical solution of incompressible fluid flow using the pressure-based segregated algorithms such as projection methods. For unsteady flows, the pressure Poisson equation is solved at each time step usually in physical space using iterative solvers, and the resulting pressure gradient is then applied to make the velocity field divergence-free. It is generally accepted that this pressure-correction stage is the most time-consuming part of the flow solver and any meaningful acceleration would contribute significantly to the overall computational efficiency. The objective of the present work was to develop a fast hybrid pressure-correction algorithm for numerical simulation of incompressible flows around obstacles in the context of projection methods. The key idea is to adopt different numerical methods/discretisations in the sub-steps of projection methods. Here, a classical second-order time-marching projection method, which consists of two sub-steps, was chosen for the purposes of demonstration. In the first sub-step, the momentum equations were discretised on unstructured grids and solved by conventional numerical methods, here a meshless method. In the second sub-step (pressure-correction), the proposed algorithm adopts a double-discretisation system and combines the weighted least-squares approximation with the essence of immersed boundary methods. Such a design allowed us to develop an FFT-based solver to speed up the solution of the pressure Poisson equation for flow cases with obstacles, while keeping the implementation of the boundary conditions for the momentum equations as easy as conventional numerical methods do with unstructured grids. The numerical experiments of five test cases were performed to verify and validate the proposed hybrid algorithm and evaluate its computational performance. The results showed that the new FFT-based hybrid algorithm works and is robust, and it was significantly faster than the multigrid-based reference method. The hybrid algorithm opens an avenue for the development of next-generation high-performance parallel computational fluid dynamics solvers for incompressible flows. Full article
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22 pages, 5386 KiB  
Article
Modernising Receiver Operating Characteristic (ROC) Curves
by Leslie R. Pendrill, Jeanette Melin, Anne Stavelin and Gunnar Nordin
Algorithms 2023, 16(5), 253; https://doi.org/10.3390/a16050253 - 13 May 2023
Cited by 6 | Viewed by 2797
Abstract
The justification for making a measurement can be sought in asking what decisions are based on measurement, such as in assessing the compliance of a quality characteristic of an entity in relation to a specification limit, SL. The relative performance of testing [...] Read more.
The justification for making a measurement can be sought in asking what decisions are based on measurement, such as in assessing the compliance of a quality characteristic of an entity in relation to a specification limit, SL. The relative performance of testing devices and classification algorithms used in assessing compliance is often evaluated using the venerable and ever popular receiver operating characteristic (ROC). However, the ROC tool has potentially all the limitations of classic test theory (CTT) such as the non-linearity, effects of ordinality and confounding task difficulty and instrument ability. These limitations, inherent and often unacknowledged when using the ROC tool, are tackled here for the first time with a modernised approach combining measurement system analysis (MSA) and item response theory (IRT), using data from pregnancy testing as an example. The new method of assessing device ability from separate Rasch IRT regressions for each axis of ROC curves is found to perform significantly better, with correlation coefficients with traditional area-under-curve metrics of at least 0.92 which exceeds that of linearised ROC plots, such as Linacre’s, and is recommended to replace other approaches for device assessment. The resulting improved measurement quality of each ROC curve achieved with this original approach should enable more reliable decision-making in conformity assessment in many scenarios, including machine learning, where its use as a metric for assessing classification algorithms has become almost indispensable. Full article
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22 pages, 616 KiB  
Review
Impact of Digital Transformation on the Energy Sector: A Review
by Zahra Nazari and Petr Musilek
Algorithms 2023, 16(4), 211; https://doi.org/10.3390/a16040211 - 18 Apr 2023
Cited by 16 | Viewed by 11098
Abstract
Digital transformation is a phenomenon introduced by the transformative power of digital technologies, and it has become a key driver for the energy sector, with advancements in technology leading to significant changes in the way energy is produced, transmitted, and consumed. The impact [...] Read more.
Digital transformation is a phenomenon introduced by the transformative power of digital technologies, and it has become a key driver for the energy sector, with advancements in technology leading to significant changes in the way energy is produced, transmitted, and consumed. The impact of digital transformation on the energy sector is profound, with benefits such as improved efficiency, cost reduction, and enhanced customer experience. This article provides a review of the impact of digital transformation on the energy sector, highlighting key trends and emerging technologies that are transforming the sector. The article begins by defining the concept of digital transformation, describing its scope, and explaining two conceptual frameworks to provide a deep understanding of the concept. This article then explores the benefits of digital transformation, examines its impact, and identifies its enablers and barriers. Each source examined was analyzed to extract qualitative results and assess its contribution to the researched topic. This paper also acknowledges the challenges posed by digital transformation, including concerns about cybersecurity, data privacy, and workforce displacement. Finally, we discuss the potential developments that are expected in the future of digital transformation in the power sector and conclude that digital transformation has the potential to significantly improve the energy sector’s efficiency, sustainability, and resiliency. Full article
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15 pages, 396 KiB  
Article
Algorithm for Generating S-Boxes with Prescribed Differential Properties
by Stanislav Marochok and Pavol Zajac
Algorithms 2023, 16(3), 157; https://doi.org/10.3390/a16030157 - 13 Mar 2023
Cited by 4 | Viewed by 3150
Abstract
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 algorithms. These search algorithms typically generate random candidate Boolean functions (or permutations) that [...] Read more.
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 algorithms. These search algorithms typically generate random candidate Boolean functions (or permutations) that are improved during the search by examining the search space in a specific way. Here, we introduce a new type of stochastic algorithm for generating cryptographic S-boxes. We do not generate and then improve the Boolean function; instead, we build the vector of values incrementally. New values are obtained by randomized search driven by restrictions on the differential spectrum of the generated S-box. In this article, we formulate two new algorithms based on this new approach and study the better one in greater detail. We prove the correctness of the proposed algorithm and evaluate its complexity. The final part contains an experimental evaluation of the method. We show that the algorithm generates S-boxes with better properties than a random search. We believe that our approach can be extended in the future by adopting more advanced stochastic search methods. Full article
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20 pages, 1598 KiB  
Article
Properties of the Quadratic Transformation of Dual Variables
by Vladimir Krutikov, Elena Tovbis, Anatoly Bykov, Predrag Stanimirovic, Ekaterina Chernova and Lev Kazakovtsev
Algorithms 2023, 16(3), 148; https://doi.org/10.3390/a16030148 - 7 Mar 2023
Cited by 1 | Viewed by 1532
Abstract
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 transformations of dual variables that [...] Read more.
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 transformations of dual variables that enable us to obtain an unconstrained optimization problem. We investigate the previously known method of transforming the components of dual variables in the form of their modulus (modulus method). We show that in the case of using the modulus method, the degree of the degeneracy of the function increases as it approaches the optimal point. Taking into account the ambiguity of the gradient in the boundary regions of the sign change of the new dual function variables and the increase in the degree of the function degeneracy, we need to use relaxation subgradient methods (RSM) that are difficult to implement and that can solve non-smooth non-convex optimization problems with a high degree of elongation of level surfaces. We propose to use the transformation of the components of dual variables in the form of their square (quadratic method). We prove that the transformed dual function has a Lipschitz gradient with a quadratic method of transformation. This enables us to use efficient gradient methods to find the extremum. The above properties are confirmed by a computational experiment. With a quadratic transformation compared to a modulus transformation, it is possible to obtain a solution of the problem by relaxation subgradient methods and smooth function minimization methods (conjugate gradient method and quasi-Newtonian method) with higher accuracy and lower computational costs. The noted transformations of dual variables were used in the program module for calculating the maximum permissible emissions of enterprises (MPE) of the software package for environmental monitoring of atmospheric air (ERA-AIR). Full article
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28 pages, 37707 KiB  
Article
Line-Level Layout Recognition of Historical Documents with Background Knowledge
by Norbert Fischer, Alexander Hartelt and Frank Puppe
Algorithms 2023, 16(3), 136; https://doi.org/10.3390/a16030136 - 3 Mar 2023
Cited by 3 | Viewed by 3113
Abstract
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 optical character recognition (OCR) of early printed [...] Read more.
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 optical character recognition (OCR) of early printed documents. This paper describes and evaluates how deep learning approaches recognize text lines and can be extended to layout recognition using background knowledge. The evaluation was performed on five corpora of early prints from the 15th and 16th Centuries, representing a variety of layout features. While the main text with standard layouts could be recognized in the correct reading order with a precision and recall of up to 99.9%, also complex layouts were recognized at a rate as high as 90% by using background knowledge, the full potential of which was revealed if many pages of the same source were transcribed. Full article
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17 pages, 9172 KiB  
Article
Rapid Prototyping of H∞ Algorithm for Real-Time Displacement Volume Control of Axial Piston Pumps
by Alexander Mitov, Tsonyo Slavov and Jordan Kralev
Algorithms 2023, 16(2), 120; https://doi.org/10.3390/a16020120 - 15 Feb 2023
Cited by 4 | Viewed by 2320
Abstract
A system for the rapid prototyping of real-time control algorithms for open-circuit variable displacement axial-piston pumps is presented. In order to establish real-time control, and communication and synchronization with the programmable logic controller of an axial piston pump, the custom CAN communication protocol [...] Read more.
A system for the rapid prototyping of real-time control algorithms for open-circuit variable displacement axial-piston pumps is presented. In order to establish real-time control, and communication and synchronization with the programmable logic controller of an axial piston pump, the custom CAN communication protocol is developed. This protocol is realized as a Simulink® S-function, which is a part of main Simulink® model. This model works in real-time and allows for the implementation of rapid prototyping of various control strategies including advanced algorithms such as H∞ control. The aim of the algorithm is to achieve control system performance in the presence of various load disturbances with an admissible control signal rate and amplitude. In contrast to conventional systems, the developed solution suggests using an embedded approach for the prototyping of various algorithms. The obtained results show the advantages of the designed H∞ controller that ensure the robustness of a closed-loop system in the presence of significant load disturbances. These type of systems with displacement volume regulation are important for industrial hydraulic drive systems with relatively high power. Full article
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23 pages, 1523 KiB  
Article
Cathode Shape Design for Steady-State Electrochemical Machining
by Jinming Lu and Ewald A. Werner
Algorithms 2023, 16(2), 67; https://doi.org/10.3390/a16020067 - 19 Jan 2023
Cited by 1 | Viewed by 2340
Abstract
The inverse or cathode shape design problem of electrochemical machining (ECM) deals with the computation of the shape of the tool cathode required for producing a workpiece anode of a desired shape. This work applied the complex variable method and the continuous adjoint-based [...] Read more.
The inverse or cathode shape design problem of electrochemical machining (ECM) deals with the computation of the shape of the tool cathode required for producing a workpiece anode of a desired shape. This work applied the complex variable method and the continuous adjoint-based shape optimization method to solve the steady-state cathode shape design problem with anode shapes of different smoothnesses. An exact solution to the cathode shape design problem is proven to exist only in cases when the function describing the anode shape is analytic. The solution’s physical realizability is shown to depend on the aspect ratio of features on the anode surface and the width of the standard equilibrium front gap. In cases where an exact and physically realizable cathode shape exists, the continuous adjoint-based shape optimization method is shown to produce accurate numerical solutions; otherwise, the method produces cathode shapes with singularities. For the latter cases, the work demonstrates how perimeter regularization can be applied to compute smooth approximate cathode shapes suitable for producing workpieces within the range of manufacturing tolerance. Full article
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15 pages, 1713 KiB  
Article
Set-Point Control of a Spatially Distributed Buck Converter
by Klaus Röbenack and Stefan Palis
Algorithms 2023, 16(1), 55; https://doi.org/10.3390/a16010055 - 13 Jan 2023
Cited by 4 | Viewed by 1701
Abstract
The classical buck converter is a very common DC–DC converter, which reduces an higher input supply voltage to a lower output load voltage. Replacing the inductor and the capacitor by a transmission line, we obtain a distributed buck converter, which can be described [...] Read more.
The classical buck converter is a very common DC–DC converter, which reduces an higher input supply voltage to a lower output load voltage. Replacing the inductor and the capacitor by a transmission line, we obtain a distributed buck converter, which can be described by partial differential equations. Therefore, we obtain a completely new class of model. This new topology can be used if the load is operated at some spatial distance from the power supply, where the power supply line is directly used as a reactive network element of the converter. In addition to the analysis and simulation we will also investigate the control of such a converter. In this contribution, we employ a discrepancy-based control technique. Approximating the theoretically derived feedback law yields an easy to implement sliding mode control scheme. The controller design is based on an ideal circuit model and verified by numerical simulation. Full article
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15 pages, 505 KiB  
Article
An Algorithm for Solving Zero-Sum Differential Game Related to the Nonlinear H Control Problem
by Vladimir Milić, Josip Kasać and Marin Lukas
Algorithms 2023, 16(1), 48; https://doi.org/10.3390/a16010048 - 10 Jan 2023
Cited by 1 | Viewed by 2364
Abstract
This paper presents an approach for the solution of a zero-sum differential game associated with a nonlinear state-feedback H control problem. Instead of using the approximation methods for solving the corresponding Hamilton–Jacobi–Isaacs (HJI) partial differential equation, we propose an algorithm that calculates [...] Read more.
This paper presents an approach for the solution of a zero-sum differential game associated with a nonlinear state-feedback H control problem. Instead of using the approximation methods for solving the corresponding Hamilton–Jacobi–Isaacs (HJI) partial differential equation, we propose an algorithm that calculates the explicit inputs to the dynamic system by directly performing minimization with simultaneous maximization of the same objective function. In order to achieve numerical robustness and stability, the proposed algorithm uses: quasi-Newton method, conjugate gradient method, line search method with Wolfe conditions, Adams approximation method for time discretization and complex-step calculation of derivatives. The algorithm is evaluated in computer simulations on examples of first- and second-order nonlinear systems with analytical solutions of H control problem. Full article
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14 pages, 349 KiB  
Article
Hyperparameter Black-Box Optimization to Improve the Automatic Classification of Support Tickets
by Renato Bruni, Gianpiero Bianchi and Pasquale Papa
Algorithms 2023, 16(1), 46; https://doi.org/10.3390/a16010046 - 10 Jan 2023
Cited by 1 | Viewed by 2157
Abstract
User requests to a customer service, also known as tickets, are essentially short texts in natural language. They should be grouped by topic to be answered efficiently. The effectiveness increases if this semantic categorization becomes automatic. We pursue this goal by using text [...] Read more.
User requests to a customer service, also known as tickets, are essentially short texts in natural language. They should be grouped by topic to be answered efficiently. The effectiveness increases if this semantic categorization becomes automatic. We pursue this goal by using text mining to extract the features from the tickets, and classification to perform the categorization. This is however a difficult multi-class problem, and the classification algorithm needs a suitable hyperparameter configuration to produce a practically useful categorization. As recently highlighted by several researchers, the selection of these hyperparameters is often the crucial aspect. Therefore, we propose to view the hyperparameter choice as a higher-level optimization problem where the hyperparameters are the decision variables and the objective is the predictive performance of the classifier. However, an explicit analytical model of this problem cannot be defined. Therefore, we propose to solve it as a black-box model by means of derivative-free optimization techniques. We conduct experiments on a relevant application: the categorization of the requests received by the Contact Center of the Italian National Statistics Institute (Istat). Results show that the proposed approach is able to effectively categorize the requests, and that its performance is increased by the proposed hyperparameter optimization. Full article
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2022

Jump to: 2024, 2023

11 pages, 353 KiB  
Article
On the Semi-Local Convergence of Two Competing Sixth Order Methods for Equations in Banach Space
by Ioannis K. Argyros, Stepan Shakhno, Samundra Regmi and Halyna Yarmola
Algorithms 2023, 16(1), 2; https://doi.org/10.3390/a16010002 - 20 Dec 2022
Viewed by 1582
Abstract
A plethora of methods are used for solving equations in the finite-dimensional Euclidean space. Higher-order derivatives, on the other hand, are utilized in the calculation of the local convergence order. However, these derivatives are not on the methods. Moreover, no bounds on the [...] Read more.
A plethora of methods are used for solving equations in the finite-dimensional Euclidean space. Higher-order derivatives, on the other hand, are utilized in the calculation of the local convergence order. However, these derivatives are not on the methods. Moreover, no bounds on the error and uniqueness information for the solution are given either. Thus, the advantages of these methods are restricted in their application to equations with operators that are sufficiently many times differentiable. These limitations motivate us to write this paper. In particular, we present the more interesting semi-local convergence analysis not given previously for two sixth-order methods that are run under the same set of conditions. The technique is based on the first derivative that only appears in the methods. This way, these methods are more applicable for addressing equations and in the more general setting of Banach space-valued operators. Hence, the applicability is extended for these methods. This is the novelty of the paper. The same technique can be used in other methods. Finally, examples are used to test the convergence of the methods. Full article
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18 pages, 1952 KiB  
Article
A Proposal of Printed Table Digitization Algorithm with Image Processing
by Chenrui Shi, Nobuo Funabiki, Yuanzhi Huo, Mustika Mentari, Kohei Suga and Takashi Toshida
Algorithms 2022, 15(12), 471; https://doi.org/10.3390/a15120471 - 11 Dec 2022
Viewed by 2252
Abstract
Nowadays, digital transformation (DX) is the key concept to change and improve the operations in governments, companies, and schools. Therefore, any data should be digitized for processing by computers. Unfortunately, a lot of data and information are printed and handled on paper, although [...] Read more.
Nowadays, digital transformation (DX) is the key concept to change and improve the operations in governments, companies, and schools. Therefore, any data should be digitized for processing by computers. Unfortunately, a lot of data and information are printed and handled on paper, although they may originally come from digital sources. Data on paper can be digitized using an optical character recognition (OCR) software. However, if the paper contains a table, it becomes difficult because of the separated characters by rows and columns there. It is necessary to solve the research question of “how to convert a printed table on paper into an Excel table while keeping the relationships between the cells?” In this paper, we propose a printed table digitization algorithm using image processing techniques and OCR software for it. First, the target paper is scanned into an image file. Second, each table is divided into a collection of cells where the topology information is obtained. Third, the characters in each cell are digitized by OCR software. Finally, the digitalized data are arranged in an Excel file using the topology information. We implement the algorithm on Python using OpenCV for the image processing library and Tesseract for the OCR software. For evaluations, we applied the proposal to 19 scanned and 17 screenshotted table images. The results show that for any image, the Excel file is generated with the correct structure, and some characters are misrecognized by OCR software. The improvement will be in future works. Full article
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17 pages, 5842 KiB  
Article
Cell Fault Identification and Localization Procedure for Lithium-Ion Battery System of Electric Vehicles Based on Real Measurement Data
by Szabolcs Kocsis Szürke, Gergő Sütheö, Antal Apagyi, István Lakatos and Szabolcs Fischer
Algorithms 2022, 15(12), 467; https://doi.org/10.3390/a15120467 - 8 Dec 2022
Cited by 5 | Viewed by 2441
Abstract
Vehicle safety risk can be decreased by diagnosing the lithium-ion battery system of electric road vehicles. Real-time cell diagnostics can avoid unexpected occurrences. However, lithium-ion batteries in electric vehicles can significantly differ in design, capacity, and chemical composition. In addition, the battery monitoring [...] Read more.
Vehicle safety risk can be decreased by diagnosing the lithium-ion battery system of electric road vehicles. Real-time cell diagnostics can avoid unexpected occurrences. However, lithium-ion batteries in electric vehicles can significantly differ in design, capacity, and chemical composition. In addition, the battery monitoring systems of the various vehicles are also diverse, so communication across the board is not available or can only be achieved with significant difficulty. Hence, unique type-dependent data queries and filtering are necessary in most cases. In this paper, a Volkswagen e-Golf electric vehicle is investigated; communication with the vehicle was implemented via an onboard diagnostic port (so-called OBD), and the data stream was recorded. The goal of the research is principally to filter out, identify, and localize defective/weak battery cells. Numerous test cycles (constant and dynamic measurements) were carried out to identify cell abnormalities (so-called deviations). A query and data filtering process was designed to detect defective battery cells. The fault detection procedure is based on several cell voltage interruptions at various loading levels. The methodology demonstrated in this article uses a fault diagnosis technique based on voltage abnormalities. In addition, it employs a hybrid algorithm that executes calculations on measurement and recorded data. In the evaluation, a status line comprising three different categories was obtained by parametrizing and prioritizing (weighting) the individual measured values. It allows the cells to be divided into the categories green (adequate region), yellow (to be monitored), and red (possible error). In addition, several querying strategies were developed accordingly to clarify and validate the measurement results. The several strategies were examined individually and analyzed for their strengths and weaknesses. Based on the results, a data collection, processing, and evaluation strategy for an electric vehicle battery system have been developed. The advantage of the developed algorithm is that the method can be adapted to any electric or hybrid vehicle battery. Full article
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14 pages, 10628 KiB  
Article
Error Investigation on Wi-Fi RTT in Commercial Consumer Devices
by Yinhuan Dong, Duanxu Shi, Tughrul Arslan and Yunjie Yang
Algorithms 2022, 15(12), 464; https://doi.org/10.3390/a15120464 - 7 Dec 2022
Cited by 3 | Viewed by 2278
Abstract
Researchers have explored multiple Wi-Fi features to estimate user locations in indoor environments in the past decade, such as Received Signal Strength Indication (RSSI), Channel State Information (CSI), Time of Arrival (TOA), and Angle of Arrive (AoA). Fine Time Measurement (FTM) is a [...] Read more.
Researchers have explored multiple Wi-Fi features to estimate user locations in indoor environments in the past decade, such as Received Signal Strength Indication (RSSI), Channel State Information (CSI), Time of Arrival (TOA), and Angle of Arrive (AoA). Fine Time Measurement (FTM) is a protocol standardized by IEEE 802.11-2016, which can estimate the distance between the initiator and the station using Wi-Fi Round-Trip Time (RTT). Promoted by Google, such a protocol has been explored in many mobile localization algorithms, which can provide meter-level positioning accuracy between Wi-Fi RTT-enabled smartphones and access points (APs). However, previous studies have shown that the Wi-Fi RTT measurements are sensitive to environmental changes, which leads to significant errors in the localization algorithms. Such an error usually varies according to different environments and settings. Therefore, this paper investigates the error in Wi-Fi RTT distance measurements by setting multiple experiments with different hardware, motion status, and signal path loss conditions. The experiment results show that four categories of errors are found in RTT distance measurements, including hardware-dependent bias, blocker-dependent bias, fluctuations, and outliers. Comparison and analysis are carried out to illustrate the impact of the different errors on Wi-Fi RTT distance. Full article
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12 pages, 709 KiB  
Article
Numerical Integration Schemes Based on Composition of Adjoint Multistep Methods
by Dmitriy Pesterev, Olga Druzhina, Alexander Pchelintsev, Erivelton Nepomuceno and Denis Butusov
Algorithms 2022, 15(12), 463; https://doi.org/10.3390/a15120463 - 7 Dec 2022
Cited by 2 | Viewed by 1718
Abstract
A composition is a powerful tool for obtaining new numerical methods for solving differential equations. Composition ODE solvers are usually based on single-step basic methods applied with a certain set of step coefficients. However, multistep composition schemes are much less-known and investigated in [...] Read more.
A composition is a powerful tool for obtaining new numerical methods for solving differential equations. Composition ODE solvers are usually based on single-step basic methods applied with a certain set of step coefficients. However, multistep composition schemes are much less-known and investigated in the literature due to their complex nature. In this paper, we propose several novel schemes for solving ordinary differential equations based on the composition of adjoint multistep methods. Numerical stability, energy preservation, and performance of proposed schemes are investigated theoretically and experimentally using a set of differential problems. The applicability and efficiency of the proposed composition multistep methods are discussed. Full article
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16 pages, 394 KiB  
Article
Mixed Alternating Projections with Application to Hankel Low-Rank Approximation
by Nikita Zvonarev and Nina Golyandina
Algorithms 2022, 15(12), 460; https://doi.org/10.3390/a15120460 - 5 Dec 2022
Cited by 1 | Viewed by 1518
Abstract
The method of alternating projections for extracting low-rank signals is considered. The problem of decreasing the computational costs while keeping the estimation accuracy is analyzed. The proposed algorithm consists of alternating projections on the set of low-rank matrices and the set of Hankel [...] Read more.
The method of alternating projections for extracting low-rank signals is considered. The problem of decreasing the computational costs while keeping the estimation accuracy is analyzed. The proposed algorithm consists of alternating projections on the set of low-rank matrices and the set of Hankel matrices, where iterations of weighted projections with different weights are mixed. For algorithm justification, theory related to mixed alternating projections to linear subspaces is studied and the limit of mixed projections is obtained. The proposed approach is applied to the problem of Hankel low-rank approximation for constructing a modification of the Cadzow algorithm. Numerical examples compare the accuracy and computational cost of the proposed algorithm and Cadzow iterations. Full article
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27 pages, 1576 KiB  
Article
Clustering Algorithm with a Greedy Agglomerative Heuristic and Special Distance Measures
by Guzel Shkaberina, Leonid Verenev, Elena Tovbis, Natalia Rezova and Lev Kazakovtsev
Algorithms 2022, 15(6), 191; https://doi.org/10.3390/a15060191 - 1 Jun 2022
Cited by 2 | Viewed by 3192
Abstract
Automatic grouping (clustering) involves dividing a set of objects into subsets (groups) so that the objects from one subset are more similar to each other than to the objects from other subsets according to some criterion. Kohonen neural networks are a class of [...] Read more.
Automatic grouping (clustering) involves dividing a set of objects into subsets (groups) so that the objects from one subset are more similar to each other than to the objects from other subsets according to some criterion. Kohonen neural networks are a class of artificial neural networks, the main element of which is a layer of adaptive linear adders, operating on the principle of “winner takes all”. One of the advantages of Kohonen networks is their ability of online clustering. Greedy agglomerative procedures in clustering consistently improve the result in some neighborhood of a known solution, choosing as the next solution the option that provides the least increase in the objective function. Algorithms using the agglomerative greedy heuristics demonstrate precise and stable results for a k-means model. In our study, we propose a greedy agglomerative heuristic algorithm based on a Kohonen neural network with distance measure variations to cluster industrial products. Computational experiments demonstrate the comparative efficiency and accuracy of using the greedy agglomerative heuristic in the problem of grouping of industrial products into homogeneous production batches. Full article
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