Algorithms

2025

Jump to: 2024, 2023

29 pages, 1821 KiB

Open AccessArticle

Learning Analytics in a Non-Linear Virtual Course

by Jhon Mercado, Carlos Mendoza-Cardenas, Luis Fletscher and Natalia Gaviria-Gomez

Algorithms 2025, 18(5), 284; https://doi.org/10.3390/a18050284 - 13 May 2025

Viewed by 168

Abstract

Researchers have extensively explored learning analytics in online courses, primarily focusing on linear course structures where students progress sequentially through lessons and assessments. However, non-linear courses, which allow students to complete tasks in any order, present unique challenges for learning analytics due to [...] Read more.

Researchers have extensively explored learning analytics in online courses, primarily focusing on linear course structures where students progress sequentially through lessons and assessments. However, non-linear courses, which allow students to complete tasks in any order, present unique challenges for learning analytics due to the variability in course progression among students. This study proposes a method for applying learning analytics to non-linear, self-paced MOOC-style courses, addressing early performance prediction and online learning pattern detection. The novelty of our approach lies in introducing a personalized feature aggregation that adapts to each student’s progress rather than being defined at fixed timelines. We evaluated three types of features—engagement, behavior, and performance—using data from a non-linear large-scale Moodle course designed to prepare high school students for a public university entrance exam. Our approach predicted early student performance, achieving an F1-score of 0.73 at a 20% cumulative weight assessment. Feature importance analysis revealed that performance and behavior were the strongest predictors, while engagement features, such as time spent on educational resources, also played a significant role. In addition to performance prediction, we conducted a clustering analysis that identified four distinct online learning patterns recurring across various cumulative weight assessments. These patterns provide valuable insights into student behavior and performance and have practical implications, enabling educators to deliver more personalized feedback and targeted interventions to meet individual student needs. Full article

► Show Figures

Figure 1

52 pages, 748 KiB

Open AccessSystematic Review

Advancements in Non-Destructive Detection of Biochemical Traits in Plants Through Spectral Imaging-Based Algorithms: A Systematic Review

by Aleksander Dabek, Lorenzo Mantovani, Susanna Mirabella, Michele Vignati and Simone Cinquemani

Algorithms 2025, 18(5), 255; https://doi.org/10.3390/a18050255 - 27 Apr 2025

Viewed by 286

Abstract

This paper provides a comprehensive overview of the state of the art non-destructive methods for detecting plant biochemical traits through spectral imaging of leafy greens. It offers insights into the various detection techniques and their effectiveness. The review emphasizes the algorithms used for [...] Read more.

This paper provides a comprehensive overview of the state of the art non-destructive methods for detecting plant biochemical traits through spectral imaging of leafy greens. It offers insights into the various detection techniques and their effectiveness. The review emphasizes the algorithms used for spectral data analysis, highlighting advancements in computational methods that have contributed to improving detection accuracy and efficiency. This systematic review, following the PRISMA 2020 guidelines, explores the applications of non-destructive measurements, techniques, and algorithms, including hyperspectral imaging and spectrometry for detecting a wide range of chemical compounds and elements in lettuce, basil, and spinach. This review focuses on studies published from 2019 onward, focusing on the detection of compounds such as chlorophyll, carotenoids, nitrogen, nitrate, and anthocyanin. Additional compounds such as phosphorus, vitamin C, magnesium, glucose, sugar, water content, calcium, soluble solid content, sulfur, and pH are also mentioned, although they were not the primary focus of this study. The techniques used are showcased and highlighted for each compound, and the accuracies achieved are presented to demonstrate effective detection. Full article

► Show Figures

Figure 1

62 pages, 10751 KiB

Open AccessReview

Unmanned Aerial Vehicles (UAV) Networking Algorithms: Communication, Control, and AI-Based Approaches

by Mien L. Trinh, Dung T. Nguyen, Long Q. Dinh, Mui D. Nguyen, De Rosal Ignatius Moses Setiadi and Minh T. Nguyen

Algorithms 2025, 18(5), 244; https://doi.org/10.3390/a18050244 - 24 Apr 2025

Viewed by 871

Abstract

This paper focuses on algorithms and technologies for unmanned aerial vehicles (UAVs) networking across different fields of applications. Given the limitations of UAVs in both computations and communications, UAVs usually need algorithms for either low latency or energy efficiency. In addition, coverage problems [...] Read more.

This paper focuses on algorithms and technologies for unmanned aerial vehicles (UAVs) networking across different fields of applications. Given the limitations of UAVs in both computations and communications, UAVs usually need algorithms for either low latency or energy efficiency. In addition, coverage problems should be considered to improve UAV deployment in many monitoring or sensing applications. Hence, this work firstly addresses common applications of UAV groups or swarms. Communication routing protocols are then reviewed, as they can make UAVs capable of supporting these applications. Furthermore, control algorithms are examined to ensure UAVs operate in optimal positions for specific purposes. AI-based approaches are considered to enhance UAV performance. We provide either the latest work or evaluations of existing results that can suggest suitable solutions for specific practical applications. This work can be considered as a comprehensive survey for both general and specific problems associated with UAVs in monitoring and sensing fields. Full article

► Show Figures

Figure 1

18 pages, 448 KiB

Open AccessArticle

User Armor: An Extension for AppArmor

by Mario Alviano and Pierpaolo Sestito

Algorithms 2025, 18(4), 185; https://doi.org/10.3390/a18040185 - 24 Mar 2025

Viewed by 447

Abstract

AppArmor is a mandatory access control (MAC) system for Linux based on profiles. It focuses on protecting processes, without differentiating profiles based on the users running the processes themselves. Moreover, it does not implement inheritance mechanisms to simplify the management of profiles and [...] Read more.

AppArmor is a mandatory access control (MAC) system for Linux based on profiles. It focuses on protecting processes, without differentiating profiles based on the users running the processes themselves. Moreover, it does not implement inheritance mechanisms to simplify the management of profiles and avoid the duplication of rules. This work introduces UserArmor, an extension of AppArmor that overcomes the aforementioned limitations by allowing specific profiles to be associated with users and implementing an inheritance system to reduce complexity, improve reusability, and ensure consistency in security rules. An application to Answer Set Programming is discussed. Full article

► Show Figures

Figure 1

19 pages, 5390 KiB

Open AccessArticle

A Continuous Monitoring and Reallocation Method for Successful Decisions in Change Management

by Fotios Panagiotopoulos and Vassilios Chatzis

Algorithms 2025, 18(4), 184; https://doi.org/10.3390/a18040184 - 24 Mar 2025

Viewed by 228

Abstract

Businesses and organizations often struggle to cope in a rapidly changing and competitive environment, requiring changes with increasing frequency and complexity. The evolution of information systems has enabled direct access to information and data, which can be utilized for the effective implementation of [...] Read more.

Businesses and organizations often struggle to cope in a rapidly changing and competitive environment, requiring changes with increasing frequency and complexity. The evolution of information systems has enabled direct access to information and data, which can be utilized for the effective implementation of changes. This usually requires managing resistance to change, which is often presented by employees. The aim of this study is to address the problem of change management in order to limit the decline in overall performance during the critical period of change and to accelerate the implementation of change. This study provides a new innovative approach to managing employee resistance during the change process based on a continuous monitoring and reallocation algorithm. The proposed method introduces the idea of solving the human resource allocation problem by continuously readjusting staff allocation during the change process. The Hungarian algorithm is used to optimize assignments. In this way, the resistance of each employee is taken into account regularly, and the assignment can be altered in the early stages of change. The new method is mathematically formulated and described in detail through an algorithm, which is then used in experiments. The proposed method of frequently reallocating human resources to tasks leads to better overall performance and improves decision making during change processes. The experimental results show that the new approach significantly increases the total performance by up to 124% when compared to existing change management approaches and reduces the time required to achieve the desired state by up to 20%. Thus, the enhanced management of human resistance to change provides distinct advantages over traditional methods by ensuring more dynamic, timely, and adaptive resource allocation during the change period, ultimately leading to successful decision making and sustainable change management. Full article

► Show Figures

Figure 1

2024

Jump to: 2025, 2023

31 pages, 3360 KiB

Open AccessArticle

IMM Filtering Algorithms for a Highly Maneuvering Fighter Aircraft: An Overview

by M. N. Radhika, Mahendra Mallick and Xiaoqing Tian

Algorithms 2024, 17(9), 399; https://doi.org/10.3390/a17090399 - 6 Sep 2024

Cited by 1 | Viewed by 1401

Abstract

The trajectory estimation of a highly maneuvering target is a challenging problem and has practical applications. The interacting multiple model (IMM) filter is a well-established filtering algorithm for the trajectory estimation of maneuvering targets. In this study, we present an overview of IMM [...] Read more.

The trajectory estimation of a highly maneuvering target is a challenging problem and has practical applications. The interacting multiple model (IMM) filter is a well-established filtering algorithm for the trajectory estimation of maneuvering targets. In this study, we present an overview of IMM filtering algorithms for tracking a highly-maneuverable fighter aircraft using an air moving target indicator (AMTI) radar on another aircraft. This problem is a nonlinear filtering problem due to nonlinearities in the dynamic and measurement models. We first describe single-model nonlinear filtering algorithms: the extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF). Then, we summarize the IMM-based EKF (IMM-EKF), IMM-based UKF (IMM-UKF), and IMM-based CKF (CKF). In order to compare the state estimation accuracies of the IMM-based filters, we present a derivation of the posterior Cramér-Rao lower bound (PCRLB). We consider fighter aircraft traveling with accelerations 3g, 4g, 5g, and 6g and present numerical results for state estimation accuracy and computational cost under various operating conditions. Our results show that under normal operating conditions, the three IMM-based filters have nearly the same accuracy. This is due to the accuracy of the measurements of the AMTI radar and the high data rate. Full article

► Show Figures

Figure 1

19 pages, 1787 KiB

Open AccessArticle

Algorithms of Cross-Domain Redundancy Management for Resilient of Dual-Priority Critical Communication Systems

by Igor Kabashkin

Algorithms 2024, 17(9), 386; https://doi.org/10.3390/a17090386 - 2 Sep 2024

Viewed by 2207

Abstract

The paper presents models for managing cross-domain redundancy to enhance the reliability of two priority communication channels within critical infrastructure systems. Employing Markov chain models, the paper analyzes the impact of two distinct redundancy management strategies: a unified reserve pool and a separate [...] Read more.

The paper presents models for managing cross-domain redundancy to enhance the reliability of two priority communication channels within critical infrastructure systems. Employing Markov chain models, the paper analyzes the impact of two distinct redundancy management strategies: a unified reserve pool and a separate pool approach with cross-domain resource sharing. The study introduces reliability improvement factors to quantify system performance, exploring their dependency on the number of additional redundant elements, their inherent reliability, and the chosen strategy for managing cross-domain redundancy. An air traffic control system serves as a case study of the application of the proposed management algorithms. Results indicate that the integration of resources from different priority domains significantly improves communication reliability. The findings may be useful for the design and operation of secure communication networks. Full article

► Show Figures

Figure 1

23 pages, 1362 KiB

Open AccessArticle

Joint Optimization of Service Migration and Resource Allocation in Mobile Edge–Cloud Computing

by Zhenli He, Liheng Li, Ziqi Lin, Yunyun Dong, Jianglong Qin and Keqin Li

Algorithms 2024, 17(8), 370; https://doi.org/10.3390/a17080370 - 21 Aug 2024

Viewed by 1707

Abstract

In the rapidly evolving domain of mobile edge–cloud computing (MECC), the proliferation of Internet of Things (IoT) devices and mobile applications poses significant challenges, particularly in dynamically managing computational demands and user mobility. Current research has partially addressed aspects of service migration and [...] Read more.

In the rapidly evolving domain of mobile edge–cloud computing (MECC), the proliferation of Internet of Things (IoT) devices and mobile applications poses significant challenges, particularly in dynamically managing computational demands and user mobility. Current research has partially addressed aspects of service migration and resource allocation, yet it often falls short in thoroughly examining the nuanced interdependencies between migration strategies and resource allocation, the consequential impacts of migration delays, and the intricacies of handling incomplete tasks during migration. This study advances the discourse by introducing a sophisticated framework optimized through a deep reinforcement learning (DRL) strategy, underpinned by a Markov decision process (MDP) that dynamically adapts service migration and resource allocation strategies. This refined approach facilitates continuous system monitoring, adept decision making, and iterative policy refinement, significantly enhancing operational efficiency and reducing response times in MECC environments. By meticulously addressing these previously overlooked complexities, our research not only fills critical gaps in the literature but also enhances the practical deployment of edge computing technologies, contributing profoundly to both theoretical insights and practical implementations in contemporary digital ecosystems. Full article

► Show Figures

Figure 1

23 pages, 1255 KiB

Open AccessArticle

The Weighted Least-Squares Approach to State Estimation in Linear State Space Models: The Case of Correlated Noise Terms

by Andreas Galka

Algorithms 2024, 17(5), 194; https://doi.org/10.3390/a17050194 - 4 May 2024

Cited by 1 | Viewed by 1330

Abstract

In this article, a particular approach to deriving recursive state estimators for linear state space models is generalised, namely the weighted least-squares approach introduced by Duncan and Horn in 1972, for the case of the two noise processes arising in such models being [...] Read more.

In this article, a particular approach to deriving recursive state estimators for linear state space models is generalised, namely the weighted least-squares approach introduced by Duncan and Horn in 1972, for the case of the two noise processes arising in such models being cross-correlated; in this context, the fact that in the available literature two different non-equivalent recursive algorithms are presented for the task of state estimation in the aforementioned case is discussed. Although the origin of the difference between these two algorithms can easily be identified, the issue has only rarely been discussed so far. Then the situations in which each of the two algorithms apply are explored, and a generalised Kalman filter which represents a merger of the two original algorithms is proposed. While, strictly speaking, optimal state estimates can be obtained only through the non-recursive weighted least-squares approach, in examples of modelling simulated and real-world data, the recursive generalised Kalman filter shows almost as good performance as the optimal non-recursive filter. Full article

► Show Figures

Figure 1

16 pages, 975 KiB

Open AccessArticle

Resource Allocation of Cooperative Alternatives Using the Analytic Hierarchy Process and Analytic Network Process with Shapley Values

by Jih-Jeng Huang and Chin-Yi Chen

Algorithms 2024, 17(4), 152; https://doi.org/10.3390/a17040152 - 5 Apr 2024

Cited by 2 | Viewed by 1831

Abstract

Cooperative alternatives need complex multi-criteria decision-making (MCDM) consideration, especially in resource allocation, where the alternatives exhibit interdependent relationships. Traditional MCDM methods like the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) often overlook the synergistic potential of cooperative alternatives. This study introduces [...] Read more.

Cooperative alternatives need complex multi-criteria decision-making (MCDM) consideration, especially in resource allocation, where the alternatives exhibit interdependent relationships. Traditional MCDM methods like the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) often overlook the synergistic potential of cooperative alternatives. This study introduces a novel method integrating AHP/ANP with Shapley values, specifically designed to address this gap by evaluating alternatives on individual merits and their contributions within coalitions. Our methodology begins with defining problem structures and applying AHP/ANP to determine the criteria weights and alternatives’ scores. Subsequently, we compute Shapley values based on coalition values, synthesizing these findings to inform resource allocation decisions more equitably. A numerical example of budget allocation illustrates the method’s efficacy, revealing significant insights into resource distribution when cooperative dynamics are considered. Our results demonstrate the proposed method’s superiority in capturing the nuanced interplay between criteria and alternatives, leading to more informed urban planning decisions. This approach marks a significant advancement in MCDM, offering a comprehensive framework that incorporates both the analytical rigor of AHP/ANP and the equitable considerations of cooperative game theory through Shapley values. Full article

► Show Figures

Figure 1

13 pages, 1138 KiB

Open AccessArticle

Theoretical and Empirical Analysis of a Fast Algorithm for Extracting Polygons from Signed Distance Bounds

by Nenad Markuš and Mirko Sužnjević

Algorithms 2024, 17(4), 137; https://doi.org/10.3390/a17040137 - 27 Mar 2024

Viewed by 1362

Abstract

Recently, there has been renewed interest in signed distance bound representations due to their unique properties for 3D shape modelling. This is especially the case for deep learning-based bounds. However, it is beneficial to work with polygons in most computer graphics applications. Thus, [...] Read more.

Recently, there has been renewed interest in signed distance bound representations due to their unique properties for 3D shape modelling. This is especially the case for deep learning-based bounds. However, it is beneficial to work with polygons in most computer graphics applications. Thus, in this paper, we introduce and investigate an asymptotically fast method for transforming signed distance bounds into polygon meshes. This is achieved by combining the principles of sphere tracing (or ray marching) with traditional polygonization techniques, such as marching cubes. We provide theoretical and experimental evidence that this approach is of the

O (N^{2} log N)

computational complexity for a polygonization grid with

N^{3}

cells. The algorithm is tested on both a set of primitive shapes and signed distance bounds generated from point clouds by machine learning (and represented as neural networks). Given its speed, implementation simplicity, and portability, we argue that it could prove useful during the modelling stage as well as in shape compression for storage. Full article

► Show Figures

Figure 1

34 pages, 6530 KiB

Open AccessArticle

A Computational Platform for Automatic Signal Processing for Bender Element Sensors

by Ionuţ Dragoş Moldovan, Abdalla Almukashfi and António Gomes Correia

Algorithms 2024, 17(4), 131; https://doi.org/10.3390/a17040131 - 22 Mar 2024

Cited by 1 | Viewed by 1663

Abstract

The small strain shear modulus is an important characteristic of geomaterials that can be measured experimentally using piezoelectric sensors (bender elements). However, most conventional signal interpretation techniques are based on the visual observation of the output signal and therefore inherently subjective. Objective techniques [...] Read more.

The small strain shear modulus is an important characteristic of geomaterials that can be measured experimentally using piezoelectric sensors (bender elements). However, most conventional signal interpretation techniques are based on the visual observation of the output signal and therefore inherently subjective. Objective techniques also exist, like the cross-correlation of the input and output signals, but they lack physical insight, as they rely on the (incorrect) assumption that input and output signals are similar. This paper presents GeoHyTE, the first objective and physically consistent toolbox for the automatic processing of the output signal of bender element sensors. GeoHyTE updates a finite element model of the experiment, iteratively searching for the small strain shear modulus that maximises the correlation between the experimental and numerical output signals. The method is objective, as the results do not depend on the experience of the user, and physically consistent, as the wave propagation process is modelled in full and signals of the same nature (output) are correlated. Moreover, GeoHyTE is nearly insensitive to grossly erroneous input by the user, both in terms of the starting point of the iterative maximisation process and refinement of the finite element model. The results obtained with GeoHyTE are validated against benchmark measurements reported in the literature and experimental data obtained by the authors. A detailed statistical analysis of the results obtained with GeoHyTE and conventional interpretation techniques is also presented. Full article

► Show Figures

Figure 1

17 pages, 1904 KiB

Open AccessArticle

Personalized Advertising in E-Commerce: Using Clickstream Data to Target High-Value Customers

by Virgilijus Sakalauskas and Dalia Kriksciuniene

Algorithms 2024, 17(1), 27; https://doi.org/10.3390/a17010027 - 10 Jan 2024

Cited by 4 | Viewed by 6138

Abstract

The growing popularity of e-commerce has prompted researchers to take a greater interest in deeper understanding online shopping behavior, consumer interest patterns, and the effectiveness of advertising campaigns. This paper presents a fresh approach for targeting high-value e-shop clients by utilizing clickstream data. [...] Read more.

The growing popularity of e-commerce has prompted researchers to take a greater interest in deeper understanding online shopping behavior, consumer interest patterns, and the effectiveness of advertising campaigns. This paper presents a fresh approach for targeting high-value e-shop clients by utilizing clickstream data. We propose the new algorithm to measure customer engagement and recognizing high-value customers. Clickstream data is employed in the algorithm to compute a Customer Merit (CM) index that measures the customer’s level of engagement and anticipates their purchase intent. The CM index is evaluated dynamically by the algorithm, examining the customer’s activity level, efficiency in selecting items, and time spent in browsing. It combines tracking customers browsing and purchasing behaviors with other relevant factors: time spent on the website and frequency of visits to e-shops. This strategy proves highly beneficial for e-commerce enterprises, enabling them to pinpoint potential buyers and design targeted advertising campaigns exclusively for high-value customers of e-shops. It allows not only boosts e-shop sales but also minimizes advertising expenses effectively. The proposed method was tested on actual clickstream data from two e-commerce websites and showed that the personalized advertising campaign outperformed the non-personalized campaign in terms of click-through and conversion rate. In general, the findings suggest, that personalized advertising scenarios can be a useful tool for boosting e-commerce sales and reduce advertising cost. By utilizing clickstream data and adopting a targeted approach, e-commerce businesses can attract and retain high-value customers, leading to higher revenue and profitability. Full article

► Show Figures

Figure 1

2023

Jump to: 2025, 2024

24 pages, 3816 KiB

Open AccessArticle

Search on an NK Landscape with Swarm Intelligence: Limitations and Future Research Opportunities

by Ren-Raw Chen, Cameron D. Miller and Puay Khoon Toh

Algorithms 2023, 16(11), 527; https://doi.org/10.3390/a16110527 - 16 Nov 2023

Cited by 1 | Viewed by 1941

Abstract

Swarm intelligence has promising applications for firm search and decision-choice problems and is particularly well suited for examining how other firms influence the focal firm’s search. To evaluate search performance, researchers examining firm search through simulation models typically build a performance landscape. The [...] Read more.

Swarm intelligence has promising applications for firm search and decision-choice problems and is particularly well suited for examining how other firms influence the focal firm’s search. To evaluate search performance, researchers examining firm search through simulation models typically build a performance landscape. The NK model is the leading tool used for this purpose in the management science literature. We assess the usefulness of the NK landscape for simulated swarm search. We find that the strength of the swarm model for examining firm search and decision-choice problems—the ability to model the influence of other firms on the focal firm—is limited to the NK landscape. Researchers will need alternative ways to create a performance landscape in order to use our full swarm model in simulations. We also identify multiple opportunities—endogenous landscapes, agent-specific landscapes, incomplete information, and costly movements—that future researchers can include in landscape development to gain the maximum insights from swarm-based firm search simulations. Full article

► Show Figures

Figure 1

18 pages, 6534 KiB

Open AccessArticle

Activation Function Dynamic Averaging as a Technique for Nonlinear 2D Data Denoising in Distributed Acoustic Sensors

by Artem T. Turov, Fedor L. Barkov, Yuri A. Konstantinov, Dmitry A. Korobko, Cesar A. Lopez-Mercado and Andrei A. Fotiadi

Algorithms 2023, 16(9), 440; https://doi.org/10.3390/a16090440 - 13 Sep 2023

Cited by 17 | Viewed by 2523

Abstract

This work studies the application of low-cost noise reduction algorithms for the data processing of distributed acoustic sensors (DAS). It presents an improvement of the previously described methodology using the activation function of neurons, which enhances the speed of data processing and the [...] Read more.

This work studies the application of low-cost noise reduction algorithms for the data processing of distributed acoustic sensors (DAS). It presents an improvement of the previously described methodology using the activation function of neurons, which enhances the speed of data processing and the quality of event identification, as well as reducing spatial distortions. The possibility of using a cheaper radiation source in DAS setups is demonstrated. Optimal algorithms’ combinations are proposed for different types of the events recorded. The criterion for evaluating the effectiveness of algorithm performance was an increase in the signal-to-noise ratio (SNR). The finest effect achieved with a combination of algorithms provided an increase in SNR of 10.8 dB. The obtained results can significantly expand the application scope of DAS. Full article

► Show Figures

Figure 1

25 pages, 3816 KiB

Open AccessArticle

From Data to Human-Readable Requirements: Advancing Requirements Elicitation through Language-Transformer-Enhanced Opportunity Mining

by Pascal Harth, Orlando Jähde, Sophia Schneider, Nils Horn and Rüdiger Buchkremer

Algorithms 2023, 16(9), 403; https://doi.org/10.3390/a16090403 - 23 Aug 2023

Cited by 4 | Viewed by 2360

Abstract

In this research, we present an algorithm that leverages language-transformer technologies to automate the generation of product requirements, utilizing E-Shop consumer reviews as a data source. Our methodology combines classical natural language processing techniques with diverse functions derived from transformer concepts, including keyword [...] Read more.

In this research, we present an algorithm that leverages language-transformer technologies to automate the generation of product requirements, utilizing E-Shop consumer reviews as a data source. Our methodology combines classical natural language processing techniques with diverse functions derived from transformer concepts, including keyword and summary generation. To effectively capture the most critical requirements, we employ the opportunity matrix as a robust mechanism for identifying and prioritizing urgent needs. Utilizing transformer technologies, mainly through the implementation of summarization and sentiment analysis, we can extract fundamental requirements from consumer assessments. As a practical demonstration, we apply our technology to analyze the ratings of the Amazon echo dot, showcasing our algorithm’s superiority over conventional approaches by extracting human-readable problem descriptions to identify critical user needs. The results of our study exemplify the potential of transformer-enhanced opportunity mining in advancing the requirements-elicitation processes. Our approach streamlines product improvement by extracting human-readable problem descriptions from E-Shop consumer reviews, augmenting operational efficiency, and facilitating decision-making. These findings underscore the transformative impact of incorporating transformer technologies within requirements engineering, paving the way for more effective and scalable algorithms to elicit and address user needs. Full article

► Show Figures

Figure 1

19 pages, 2769 KiB

Open AccessArticle

Testing a New “Decrypted” Algorithm for Plantower Sensors Measuring PM_2.5: Comparison with an Alternative Algorithm

by Lance Wallace

Algorithms 2023, 16(8), 392; https://doi.org/10.3390/a16080392 - 17 Aug 2023

Cited by 3 | Viewed by 1903

Abstract

Recently, a hypothesis providing a detailed equation for the Plantower CF_1 algorithm for PM_2.5 has been published. The hypothesis was originally validated using eight independent Plantower sensors in four PurpleAir PA-II monitors providing PM_2.5 estimates from a single site in 2020. [...] Read more.

Recently, a hypothesis providing a detailed equation for the Plantower CF_1 algorithm for PM_2.5 has been published. The hypothesis was originally validated using eight independent Plantower sensors in four PurpleAir PA-II monitors providing PM_2.5 estimates from a single site in 2020. If true, the hypothesis makes important predictions regarding PM_2.5 measurements using CF_1. Therefore, we test the hypothesis using 18 Plantower sensors from four datasets from two sites in later years (2021–2023). The four general models from these datasets agreed to within 10% with the original model. A competing algorithm known as “pm2.5 alt” has been published and is freely available on the PurpleAir API site. The accuracy, precision, and limit of detection for the two algorithms are compared. The CF_1 algorithm overestimates PM_2.5 by about 60–70% compared to two calibrated PurpleAir monitors using the pm2.5 alt algorithm. A requirement that the two sensors in a single monitor agree to within 20% was met by 85–99% of the data using the pm2.5 alt algorithm, but by only 22–74% of the data using the CF_1 algorithm. The limit of detection (LOD) of the CF_1 algorithm was about 10 times the LOD of the pm2.5 alt algorithm, resulting in 71% of the CF_1 data falling below the LOD, compared to 1 % for the pm2.5 alt algorithm. Full article

► Show Figures

Graphical abstract

14 pages, 1680 KiB

Open AccessArticle

An Algorithm for the Fisher Information Matrix of a VARMAX Process

by André Klein and Guy Mélard

Algorithms 2023, 16(8), 364; https://doi.org/10.3390/a16080364 - 28 Jul 2023

Cited by 2 | Viewed by 1276

Abstract

In this paper, an algorithm for Mathematica is proposed for the computation of the asymptotic Fisher information matrix for a multivariate time series, more precisely for a controlled vector autoregressive moving average stationary process, or VARMAX process. Meanwhile, we present briefly several algorithms [...] Read more.

In this paper, an algorithm for Mathematica is proposed for the computation of the asymptotic Fisher information matrix for a multivariate time series, more precisely for a controlled vector autoregressive moving average stationary process, or VARMAX process. Meanwhile, we present briefly several algorithms published in the literature and discuss the sufficient condition of invertibility of that matrix based on the eigenvalues of the process operators. The results are illustrated by numerical computations. Full article

► Show Figures

Figure 1

25 pages, 1920 KiB

Open AccessArticle

A Physicist’s View on Partial 3D Shape Matching

by Patrice Koehl and Henri Orland

Algorithms 2023, 16(7), 346; https://doi.org/10.3390/a16070346 - 18 Jul 2023

Cited by 2 | Viewed by 2462

Abstract

A new algorithm is presented to compute nonrigid, possibly partial comparisons of shapes defined by unstructured triangulations of their surfaces. The algorithm takes as input a pair of surfaces with each surface given by a distinct and unrelated triangulation. Its goal is to [...] Read more.

A new algorithm is presented to compute nonrigid, possibly partial comparisons of shapes defined by unstructured triangulations of their surfaces. The algorithm takes as input a pair of surfaces with each surface given by a distinct and unrelated triangulation. Its goal is to define a possibly partial correspondence between the vertices of the two triangulations, with a cost associated with this correspondence that can serve as a measure of the similarity of the two shapes. To find this correspondence, the vertices in each triangulation are characterized by a signature vector of features. We tested both the LD-SIFT signatures, based on the concept of spin images, and the wave kernel signatures obtained by solving the Shrödinger equation on the triangulation. A cost matrix C is constructed such that

C (k, l)

is the norm of the difference of the signature vectors of vertices k and l. The correspondence between the triangulations is then computed as the transport plan that solves the optimal transport or optimal partial transport problem between their sets of vertices. We use a statistical physics approach to solve these problems. The presentation of the proposed algorithm is complemented with examples that illustrate its effectiveness and manageable computing cost. Full article

► Show Figures

Figure 1

13 pages, 3521 KiB

Open AccessArticle

Deep Learning for Detecting Verticillium Fungus in Olive Trees: Using YOLO in UAV Imagery

by Marios Mamalis, Evangelos Kalampokis, Ilias Kalfas and Konstantinos Tarabanis

Algorithms 2023, 16(7), 343; https://doi.org/10.3390/a16070343 - 17 Jul 2023

Cited by 12 | Viewed by 4053

Abstract

The verticillium fungus has become a widespread threat to olive fields around the world in recent years. The accurate and early detection of the disease at scale could support solving the problem. In this paper, we use the YOLO version 5 model to [...] Read more.

The verticillium fungus has become a widespread threat to olive fields around the world in recent years. The accurate and early detection of the disease at scale could support solving the problem. In this paper, we use the YOLO version 5 model to detect verticillium fungus in olive trees using aerial RGB imagery captured by unmanned aerial vehicles. The aim of our paper is to compare different architectures of the model and evaluate their performance on this task. The architectures are evaluated at two different input sizes each through the most widely used metrics for object detection and classification tasks (precision, recall, mAP@0.5 and mAP@0.5:0.95). Our results show that the YOLOv5 algorithm is able to deliver good results in detecting olive trees and predicting their status, with the different architectures having different strengths and weaknesses. Full article

► Show Figures

Figure 1

28 pages, 8117 KiB

Open AccessArticle

Chatbots for Cultural Venues: A Topic-Based Approach

by Vasilis Bouras, Dimitris Spiliotopoulos, Dionisis Margaris, Costas Vassilakis, Konstantinos Kotis, Angeliki Antoniou, George Lepouras, Manolis Wallace and Vassilis Poulopoulos

Algorithms 2023, 16(7), 339; https://doi.org/10.3390/a16070339 - 14 Jul 2023

Cited by 2 | Viewed by 3578

Abstract

Digital assistants—such as chatbots—facilitate the interaction between persons and machines and are increasingly used in web pages of enterprises and organizations. This paper presents a methodology for the creation of chatbots that offer access to museum information. The paper introduces an information model [...] Read more.

Digital assistants—such as chatbots—facilitate the interaction between persons and machines and are increasingly used in web pages of enterprises and organizations. This paper presents a methodology for the creation of chatbots that offer access to museum information. The paper introduces an information model that is offered through the chatbot, which subsequently maps the museum’s modeled information to structures of DialogFlow, Google’s chatbot engine. Means for automating the chatbot generation process are also presented. The evaluation of the methodology is illustrated through the application of a real case, wherein we developed a chatbot for the Archaeological Museum of Tripolis, Greece. Full article

► Show Figures

Figure 1

22 pages, 1697 KiB

Open AccessArticle

Basis Functions for a Transient Analysis of Linear Commensurate Fractional-Order Systems

by Dalibor Biolek, Viera Biolková, Zdeněk Kolka and Zdeněk Biolek

Algorithms 2023, 16(7), 335; https://doi.org/10.3390/a16070335 - 13 Jul 2023

Cited by 2 | Viewed by 1781

Abstract

In this paper, the possibilities of expressing the natural response of a linear commensurate fractional-order system (FOS) as a linear combination of basis functions are analyzed. For all possible types of s^α-domain poles, the corresponding basis functions are found, the kernel [...] Read more.

In this paper, the possibilities of expressing the natural response of a linear commensurate fractional-order system (FOS) as a linear combination of basis functions are analyzed. For all possible types of s^α-domain poles, the corresponding basis functions are found, the kernel of which is the two-parameter Mittag–Leffler function E_α_,β, β = α. It is pointed out that there are mutually unambiguous correspondences between the basis functions of FOS and the known basis functions of the integer-order system (IOS) for α = 1. This correspondence can be used to algorithmically find analytical formulas for the impulse responses of FOS when the formulas for the characteristics of IOS are known. It is shown that all basis functions of FOS can be generated with Podlubny‘s function of type ε_k (t, c; α, α), where c and k are the corresponding pole and its multiplicity, respectively. Full article

► Show Figures

Figure 1

28 pages, 9566 KiB

Open AccessArticle

Optimized Workflow Framework in Construction Projects to Control the Environmental Properties of Soil

by Per Lindh and Polina Lemenkova

Algorithms 2023, 16(6), 303; https://doi.org/10.3390/a16060303 - 17 Jun 2023

Cited by 1 | Viewed by 2094

Abstract

To optimize the workflow of civil engineering construction in a harbour, this paper developed a framework of the contaminant leaching assessment carried out on the stabilized/solidified dredged soil material. The specimens included the sampled sediments collected from the in situ fieldwork in Arendal [...] Read more.

To optimize the workflow of civil engineering construction in a harbour, this paper developed a framework of the contaminant leaching assessment carried out on the stabilized/solidified dredged soil material. The specimens included the sampled sediments collected from the in situ fieldwork in Arendal and Kongshavn. The background levels of the concentration of pollutants were evaluated to assess the cumulative surface leaching of substances from samples over two months. The contamination of soil was assessed using a structured workflow scheme on the following toxic substances, heavy metals—As, Pb, Cd, Cr, Hg, Ni, and Zn; organic compounds—PAH-16 and PCB; and organotin compounds—TBT. The numerical computation and data analysis were applied to the results of geochemical testing creating computerised solutions to soil quality evaluation in civil engineering. Data modelling enabled the estimation of leaching of the contaminants in one year. The estimated leaching of As is 0.9153 mg/m², for Ni—2.8178 mg/m², for total PAH-16 as 0.0507 mg/m², and for TBT—0.00061 mg/m² per year. The performance of the sediments was examined with regard to permeability through a series of the controlled experiments. The environmental engineering tests were implemented in the Swedish Geotechnical Institute (SGI) in a triplicate mode over 64 days. The results were compared for several sites and showed that the amount of As is slightly higher in Kongshavn than for Arendal, while the content of Cd, Cr, and Ni is lower. For TBT, the levels are significantly lower than for those at Arendal. The algorithm of permeability tests evaluated the safety of foundation soil for construction of embankments and structures. The optimized assessment methods were applied for monitoring coastal areas through the evaluated permeability of soil and estimated leaching rates of heavy metals, PHB, PACs, and TBT in selected test sites in harbours of southern Norway. Full article

► Show Figures

Figure 1

25 pages, 8359 KiB

Open AccessArticle

Generalized Algorithm Based on Equivalent Circuits for Evaluating Shielding Effectiveness of Electronic Equipment Enclosures

by Anton A. Ivanov, Aleksey A. Kvasnikov, Alexander V. Demakov, Maxim E. Komnatnov, Sergei P. Kuksenko and Talgat R. Gazizov

Algorithms 2023, 16(6), 294; https://doi.org/10.3390/a16060294 - 8 Jun 2023

Cited by 1 | Viewed by 2317

Abstract

The article proposes a generalized algorithm for evaluating the shielding effectiveness (SE) of electronic equipment enclosures. The algorithm is based on a number of analytical models that use equivalent circuits to obtain SE values. The article begins with a brief review and interpretation [...] Read more.

The article proposes a generalized algorithm for evaluating the shielding effectiveness (SE) of electronic equipment enclosures. The algorithm is based on a number of analytical models that use equivalent circuits to obtain SE values. The article begins with a brief review and interpretation of the mathematical formulation used in the algorithm. Then, we describe the proposed algorithm using flowcharts, and we perform its validation. The validation results show that the proposed algorithm has acceptable accuracy and gives SE values comparable to numerical methods or measurements, with much less time costs. The last part of the article presents the software developed to evaluate SE based on analytical models. Full article

► Show Figures

Figure 1

16 pages, 2287 KiB

Open AccessArticle

Random forest Algorithm for the Classification of Spectral Data of Astronomical Objects

by José-Luis Solorio-Ramírez, Raúl Jiménez-Cruz, Yenny Villuendas-Rey and Cornelio Yáñez-Márquez

Algorithms 2023, 16(6), 293; https://doi.org/10.3390/a16060293 - 8 Jun 2023

Cited by 6 | Viewed by 3942

Abstract

Over time, human beings have built increasingly large astronomical observatories to increase the number of discoveries related to celestial objects. However, the amount of collected elements far exceeds the human capacity to analyze findings without help. For this reason, researchers must now turn [...] Read more.

Over time, human beings have built increasingly large astronomical observatories to increase the number of discoveries related to celestial objects. However, the amount of collected elements far exceeds the human capacity to analyze findings without help. For this reason, researchers must now turn to machine learning to analyze such data, identifying and classifying transient objects or events within extensive observations of the firmament. Algorithms from the family of random forests (an ensemble of decision trees) have become a powerful tool that can be used to classify astronomical events and objects. This work aims to illustrate the versatility of machine learning algorithms, such as decision trees, to facilitate the identification and classification of celestial bodies by manipulating hyperparameters and studying the attributes of celestial body datasets. By applying a random forest algorithm to a well-known dataset that includes three types of celestial bodies, its effectiveness was compared against some supervised classifiers of the most important approaches (Bayes, nearest neighbors, support vector machines, and neural networks). The results show that random forests are a good alternative for data analysis and classification in astronomical observations. Full article

► Show Figures

Figure 1

16 pages, 1825 KiB

Open AccessArticle

A Privacy-Preserving Symptoms Retrieval System with the Aid of Homomorphic Encryption and Private Set Intersection Schemes

by Yi-Wei Wang and Ja-Ling Wu

Algorithms 2023, 16(5), 244; https://doi.org/10.3390/a16050244 - 9 May 2023

Cited by 3 | Viewed by 2260

Abstract

This work presents an efficient and effective system allowing hospitals to share patients’ private information while ensuring that each hospital database’s medical records will not be leaked; moreover, the privacy of patients who access the data will also be protected. We assume that [...] Read more.

This work presents an efficient and effective system allowing hospitals to share patients’ private information while ensuring that each hospital database’s medical records will not be leaked; moreover, the privacy of patients who access the data will also be protected. We assume that the thread model of the hospital’s security is semi-honest (i.e., curious but honest), and each hospital hired a trusted medical records department administrator to manage patients’ private information from other hospitals. With the help of Homomorphic Encryption- and Private Set Intersection -related algorithms, our proposed system protects patient privacy, allows physicians to obtain patient information across hospitals, and prevents threats such as troublesome insider attacks and man-in-the-middle attacks. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

Feature Papers in Algorithms for Multidisciplinary Applications

Share This Topical Collection

Editor

Topical Collection Information

Keywords

Published Papers (26 papers)

2025

Jump to: 2024, 2023

2024

Jump to: 2025, 2023

2023

Jump to: 2025, 2024

Further Information

Guidelines

MDPI Initiatives

Follow MDPI