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Computation
Volume 10
Issue 9
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Computation, Volume 10, Issue 9 (September 2022) – 25 articles

Cover Story (view full-size image): Fault analysis is a cornerstone of enhancing resiliency in power grid systems so that electrical distribution companies provide a high-level service. This study aims to provide a compact yet comprehensive review of the state-of-the-art works of fault analysis in transmission power systems. We discuss fault types and several fault-analysis methodologies adopted by relevant research works, propose a novel framework to classify these works, and highlight their strengths and limitations. We anticipate that this survey would be helpful as a literature review and would benefit the research community in choosing suitable techniques for fault analysis. View this paper
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20 pages, 6416 KiB  
Article
Procedure Used to Estimate the Power Production of a Photovoltaic Module Operating under Partial Shading Conditions
by Michael Arenas-Florez, Juan David Bastidas-Rodríguez and Carlos Andres Ramos-Paja
Computation 2022, 10(9), 167; https://doi.org/10.3390/computation10090167 - 19 Sep 2022
Viewed by 1848
Abstract
This paper presents a methodology used to estimate the energy generated during one year by a photovoltaic module (PVM) operating under partial shading conditions. The methodology starts by calculating the solar paths and contours of nearby objects that produce shadows. Then, a method [...] Read more.
This paper presents a methodology used to estimate the energy generated during one year by a photovoltaic module (PVM) operating under partial shading conditions. The methodology starts by calculating the solar paths and contours of nearby objects that produce shadows. Then, a method was proposed to estimate the shading factors of each submodule. Afterwards, the solar resource data and the calculated shading factors were used to feed a detailed PVM model to calculate the power–voltage curves for each hour, which were used to obtain a power profile and estimate the energy generated by the PVM in one year. The procedure was validated through simulation and experimental results. The simulation results consider a case study available in the literature, which was simulated to evaluate the effect on the PVM energy estimation considering and disregarding the partial shading conditions. The experimental results illustrate the capacity of the proposed methodology to predict the shaded and unshaded submodules and the module power–voltage curve. The results show that the proposed method avoids the energy overestimation introduced by classical estimation methods, which affects the sizing of a photovoltaic generator. Full article
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15 pages, 8331 KiB  
Article
Dendrograms for Clustering in Multivariate Analysis: Applications for COVID-19 Vaccination Infodemic Data in Brazil
by Maria da Penha Harb, Lena Silva, Thalita Ayass, Nandamudi Vijaykumar, Marcelino Silva and Carlos Renato Francês
Computation 2022, 10(9), 166; https://doi.org/10.3390/computation10090166 - 19 Sep 2022
Cited by 3 | Viewed by 2512
Abstract
Since December 2019, with the discovery of a new coronavirus, humanity has been exposed to a large amount of information from different media. Information is not always true and official. Known as an infodemic, false information can increase the negative effects of the [...] Read more.
Since December 2019, with the discovery of a new coronavirus, humanity has been exposed to a large amount of information from different media. Information is not always true and official. Known as an infodemic, false information can increase the negative effects of the pandemic by impairing data readability and disease control. The paper aims to find similar patterns of behavior of the Brazilian population during 2021 in two analyses: with vaccination data of all age groups and using the age group of 64 years or more, representing 13% of the population, using the multivariate analysis technique. Infodemic vaccination information and pandemic numbers were also used. Dendrograms were used as a cluster visualization technique. The result of the generated clusters was verified by two algorithms: the cophenetic correlation coefficient, which obtained satisfactory results above 0.7, and the elbow method, which corroborated the number of clusters found. In the result of the analysis with all age groups, more homogeneous divisions were perceived among Brazilian states, while the second analysis resulted in more heterogeneous clusters, recalling that at the start of vaccinations they could have had fear, doubts, and significant belief in the infodemic. Full article
(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))
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29 pages, 5816 KiB  
Article
Solving the Optimal Selection of Wellness Tourist Attractions and Destinations in the GMS Using the AMIS Algorithm
by Rapeepan Pitakaso, Natthapong Nanthasamroeng, Sairoong Dinkoksung, Kantimarn Chindaprasert, Worapot Sirirak, Thanatkij Srichok, Surajet Khonjun, Sarinya Sirisan, Ganokgarn Jirasirilerd and Chaiya Chomchalao
Computation 2022, 10(9), 165; https://doi.org/10.3390/computation10090165 - 18 Sep 2022
Cited by 8 | Viewed by 5091
Abstract
This study aims to select the ideal mixture of small and medium-sized destinations and attractions in Thailand’s Ubon Ratchathani Province in order to find potential wellness destinations and attractions. In the study region, 46 attractions and destinations were developed as the service sectors [...] Read more.
This study aims to select the ideal mixture of small and medium-sized destinations and attractions in Thailand’s Ubon Ratchathani Province in order to find potential wellness destinations and attractions. In the study region, 46 attractions and destinations were developed as the service sectors for wellness tourism using the designed wellness framework and the quality level of the attractions and destinations available on social media. Distinct types of tourists, each with a different age and gender, comprise a single wellness tourist group. Due to them, even with identical attractions and sites, every traveler has a different preference. A difficult task for travel agencies is putting together combinations of attractions and places for each tourist group. In this paper, the mathematical formulation of the suggested problem is described, and the optimal solution is achieved using Lingo v.16. Unfortunately, the large size of test instances cannot be solved with Lingo v16. However, the large-scale problem, particularly the case study in the target area, has been solved using a metaheuristic method called AMIS. According to the computation in the final experiment, AMIS can raise the solution quality across all test instances by an average of 3.83 to 8.17 percent. Therefore, it can be concluded that AMIS outperformed all other strategies in discovering the ideal solution. AMIS, GA and DE may lead visitors to attractions that generate 29.76%, 29.58% and 32.20%, respectively, more revenue than they do now while keeping the same degree of preference when the number of visitors doubles. The attractions’ and destinations’ utilization has increased by 175.2 percent over the current situation. This suggests that small and medium-sized enterprises have a significantly higher chance of flourishing in the market. Full article
(This article belongs to the Special Issue Intelligent Computing, Modeling and its Applications)
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31 pages, 1203 KiB  
Article
Cayley Hash Values of Brauer Messages and Some of Their Applications in the Solutions of Systems of Differential Equations
by María Alejandra Osorio Angarita, Agustín Moreno Cañadas, Cristian Camilo Fúneme, Odette M. Mendez and Robinson-Julian Serna
Computation 2022, 10(9), 164; https://doi.org/10.3390/computation10090164 - 17 Sep 2022
Viewed by 1792
Abstract
Cayley hash values are defined by paths of some oriented graphs (quivers) called Cayley graphs, whose vertices and arrows are given by elements of a group H. On the other hand, Brauer messages are obtained by concatenating words associated with multisets constituting [...] Read more.
Cayley hash values are defined by paths of some oriented graphs (quivers) called Cayley graphs, whose vertices and arrows are given by elements of a group H. On the other hand, Brauer messages are obtained by concatenating words associated with multisets constituting some configurations called Brauer configurations. These configurations define some oriented graphs named Brauer quivers which induce a particular class of bound quiver algebras named Brauer configuration algebras. Elements of multisets in Brauer configurations can be seen as letters of the Brauer messages. This paper proves that each point (x,y)∈V=R\{0}×R\{0} has an associated Brauer configuration algebra ΛB(x,y) induced by a Brauer configuration B(x,y). Additionally, the Brauer configuration algebras associated with points in a subset of the form (⌊(x)⌋,⌈(x)⌉]×(⌊(y)⌋,⌈(y)⌉]⊂V have the same dimension. We give an analysis of Cayley hash values associated with Brauer messages M(B(x,y)) defined by a semigroup generated by some appropriated matrices A0,A1,A2∈GL(2,R) over a commutative ring R. As an application, we use Brauer messages M(B(x,y)) to construct explicit solutions for systems of linear and nonlinear differential equations of the form X″(t)+MX(t)=0 and X′(t)−X2(t)N(t)=N(t) for some suitable square matrices, M and N(t). Python routines to compute Cayley hash values of Brauer messages are also included. Full article
(This article belongs to the Special Issue Graph Theory and Its Applications in Computing)
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14 pages, 336 KiB  
Article
On Barrier Binary Options in the Telegraph-like Financial Market Model
by Nikita Ratanov
Computation 2022, 10(9), 163; https://doi.org/10.3390/computation10090163 - 17 Sep 2022
Cited by 3 | Viewed by 1614
Abstract
The article continues the study of the market model based on jump-telegraph processes. It is assumed that the price of a risky asset follows the stochastic exponential of a piecewise linear process, equipped with jumps that occur at the moments of a pattern [...] Read more.
The article continues the study of the market model based on jump-telegraph processes. It is assumed that the price of a risky asset follows the stochastic exponential of a piecewise linear process, equipped with jumps that occur at the moments of a pattern change. In this case, the standard option pricing formula was derived previously, while exotic options for this model have not yet been explored. Within this framework, we are developing procedures for pricing binary barrier options. This article concerns the “cash-(at hit)-or-nothing” binary barrier option. The main tools of this analysis are methods developed for first-pass probabilities. Some known results related to the ruin probabilities follow directly from these settings. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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11 pages, 2231 KiB  
Communication
BER Aided Energy and Spectral Efficiency Estimation in a Heterogeneous Network
by Jasmin Musovic, Adriana Lipovac and Vlatko Lipovac
Computation 2022, 10(9), 162; https://doi.org/10.3390/computation10090162 - 16 Sep 2022
Viewed by 1793
Abstract
In this work, we adopt the analysis of a heterogeneous cellular network by means of stochastic geometry, to estimate energy and spectral network efficiency. More specifically, it has been the widely spread experience that practical field assessment of the Signal-to-Noise and Interference Ratio [...] Read more.
In this work, we adopt the analysis of a heterogeneous cellular network by means of stochastic geometry, to estimate energy and spectral network efficiency. More specifically, it has been the widely spread experience that practical field assessment of the Signal-to-Noise and Interference Ratio (SINR), being the key physical-layer performance indicator, involves quite sophisticated test instrumentation that is not always available outside the lab environment. So, in this regard, we present here a simpler test model coming out of the much easier-to-measure Bit Error Rate (BER), as the latter can deteriorate due to various impairments regarded here as equivalent with additive white Gaussian noise (AWGN) abstracting (in terms of equal BER degradation) any actual non-AWGN impairment. We validated the derived analytical model for heterogeneous two-tier networks by means of an ns3 simulator, as it provided the test results that fit well to the analytically estimated corresponding ones, both indicating that small cells enable better energy and spectral efficiencies than the larger-cell networks. Full article
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11 pages, 899 KiB  
Article
Reviewing and Discussing Graph Reduction in Edge Computing Context
by Asier Garmendia-Orbegozo, José David Núñez-Gonzalez and Miguel Ángel Antón
Computation 2022, 10(9), 161; https://doi.org/10.3390/computation10090161 - 16 Sep 2022
Viewed by 1786
Abstract
Much effort has been devoted to transferring efficiently different machine-learning algorithms, and especially deep neural networks, to edge devices in order to fulfill, among others, real-time, storage and energy-consumption issues. The limited resources of edge devices and the necessity for energy saving to [...] Read more.
Much effort has been devoted to transferring efficiently different machine-learning algorithms, and especially deep neural networks, to edge devices in order to fulfill, among others, real-time, storage and energy-consumption issues. The limited resources of edge devices and the necessity for energy saving to lengthen the durability of their batteries, has encouraged an interesting trend in reducing neural networks and graphs, while keeping their predictability almost untouched. In this work, an alternative to the latest techniques for finding these reductions in networks size is proposed, seeking to figure out a simplistic way to shrink networks while maintaining, as far as possible, their predictability testing on well-known datasets. Full article
(This article belongs to the Special Issue Applications of Statistics and Machine Learning in Electronics)
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11 pages, 1942 KiB  
Article
A Linear Elasticity Theory to Analyze the Stress State of an Infinite Layer with a Cylindrical Cavity under Periodic Load
by Vitaly Miroshnikov, Basheer Younis, Oleksandr Savin and Vladimir Sobol
Computation 2022, 10(9), 160; https://doi.org/10.3390/computation10090160 - 14 Sep 2022
Cited by 3 | Viewed by 1633
Abstract
The design of parts of machines, mechanisms, structures and foundations, particularly in the aerospace industry, is closely related to the definition of the stress state of the body. The accuracy of determining the stress state is the key to optimizing the use of [...] Read more.
The design of parts of machines, mechanisms, structures and foundations, particularly in the aerospace industry, is closely related to the definition of the stress state of the body. The accuracy of determining the stress state is the key to optimizing the use of materials. Therefore, it is important to develop methods to achieve such goals. In this work, the second main spatial problem of the elasticity theory is solved for a layer with a longitudinal cylindrical cavity with periodic displacements given on the surface of the layer. The solution of the problem is based on the generalized Fourier method for a layer with a cylindrical cavity. To take into account periodic displacements, an additional problem is applied with the expansion of the solution for a layer (without a cavity) in the Fourier series. The general solution is the sum of these two solutions. The problem is reduced to an infinite system of linear algebraic equations, which is solved by the reduction method. As a result, the stress-strain state of the layer on the surface of the cavity and isthmuses from the cavity to the boundaries of the layer was obtained. The conducted numerical analysis has a high accuracy for fulfilling the boundary conditions and makes it possible to assert the physical regularity of the stress distribution, which indicates the reliability of the obtained results. The method can be applied to determine the stress-strain state of structures, whose calculation scheme is a layer with a cylindrical cavity and a given periodic displacement. Numerical results make it possible to predict the geometric parameters of the future structure. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)
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18 pages, 5596 KiB  
Article
Comparison and Evaluation of Machine Learning-Based Classification of Hand Gestures Captured by Inertial Sensors
by Ivo Stančić, Josip Musić, Tamara Grujić, Mirela Kundid Vasić and Mirjana Bonković
Computation 2022, 10(9), 159; https://doi.org/10.3390/computation10090159 - 14 Sep 2022
Cited by 3 | Viewed by 2432
Abstract
Gesture recognition is a topic in computer science and language technology that aims to interpret human gestures with computer programs and many different algorithms. It can be seen as the way computers can understand human body language. Today, the main interaction tools between [...] Read more.
Gesture recognition is a topic in computer science and language technology that aims to interpret human gestures with computer programs and many different algorithms. It can be seen as the way computers can understand human body language. Today, the main interaction tools between computers and humans are still the keyboard and mouse. Gesture recognition can be used as a tool for communication with the machine and interaction without any mechanical device such as a keyboard or mouse. In this paper, we present the results of a comparison of eight different machine learning (ML) classifiers in the task of human hand gesture recognition and classification to explore how to efficiently implement one or more tested ML algorithms on an 8-bit AVR microcontroller for on-line human gesture recognition with the intention to gesturally control the mobile robot. The 8-bit AVR microcontrollers are still widely used in the industry, but due to their lack of computational power and limited memory, it is a challenging task to efficiently implement ML algorithms on them for on-line classification. Gestures were recorded by using inertial sensors, gyroscopes, and accelerometers placed at the wrist and index finger. One thousand and eight hundred (1800) hand gestures were recorded and labelled. Six important features were defined for the identification of nine different hand gestures using eight different machine learning classifiers: Decision Tree (DT), Random Forests (RF), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM) with linear kernel, Naïve Bayes classifier (NB), K-Nearest Neighbours (KNN), and Stochastic Gradient Descent (SGD). All tested algorithms were ranged according to Precision, Recall, and F1-score (abb.: P-R-F1). The best algorithms were SVM (P-R-F1: 0.9865, 0.9861, and 0.0863), and RF (P-R-F1: 0.9863, 0.9861, and 0.0862), but their main disadvantage is their unusability for on-line implementations in 8-bit AVR microcontrollers, as proven in the paper. The next best algorithms have had only slightly poorer performance than SVM and RF: KNN (P-R-F1: 0.9835, 0.9833, and 0.9834) and LR (P-R-F1: 0.9810, 0.9810, and 0.9810). Regarding the implementation on 8-bit microcontrollers, KNN has proven to be inadequate, like SVM and RF. However, the analysis for LR has proved that this classifier could be efficiently implemented on targeted microcontrollers. Having in mind its high F1-score (comparable to SVM, RF, and KNN), this leads to the conclusion that the LR is the most suitable classifier among tested for on-line applications in resource-constrained environments, such as embedded devices based on 8-bit AVR microcontrollers, due to its lower computational complexity in comparison with other tested algorithms. Full article
(This article belongs to the Special Issue Applications of Statistics and Machine Learning in Electronics)
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16 pages, 2213 KiB  
Article
Secure Medical Image Transmission Scheme Using Lorenz’s Attractor Applied in Computer Aided Diagnosis for the Detection of Eye Melanoma
by Daniel Fernando Santos and Helbert Eduardo Espitia
Computation 2022, 10(9), 158; https://doi.org/10.3390/computation10090158 - 14 Sep 2022
Cited by 3 | Viewed by 1855
Abstract
Early detection of diseases is vital for patient recovery. This article explains the design and technical matters of a computer-supported diagnostic system for eye melanoma detection implementing a security approach using chaotic-based encryption to guarantee communication security. The system is intended to provide [...] Read more.
Early detection of diseases is vital for patient recovery. This article explains the design and technical matters of a computer-supported diagnostic system for eye melanoma detection implementing a security approach using chaotic-based encryption to guarantee communication security. The system is intended to provide a diagnosis; it can be applied in a cooperative environment for hospitals or telemedicine and can be extended to detect other types of eye diseases. The introduced method has been tested to assess the secret key, sensitivity, histogram, correlation, Number of Pixel Change Rate (NPCR), Unified Averaged Changed Intensity (UACI), and information entropy analysis. The main contribution is to offer a proposal for a diagnostic aid system for uveal melanoma. Considering the average values for 145 processed images, the results show that near-maximum NPCR values of 0.996 are obtained along with near-safe UACI values of 0.296 and high entropy of 7.954 for the ciphered images. The presented design demonstrates an encryption technique based on chaotic attractors for image transfer through the network. In this article, important theoretical considerations for implementing this system are provided, the requirements and architecture of the system are explained, and the stages in which the diagnosis is carries out are described. Finally, the encryption process is explained and the results and conclusions are presented. Full article
(This article belongs to the Special Issue Computational Medical Image Analysis)
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17 pages, 3101 KiB  
Article
Bearing Fault Diagnosis Based on Measured Data Online Processing, Domain Fusion, and ANFIS
by Quang Thinh Tran and Sy Dzung Nguyen
Computation 2022, 10(9), 157; https://doi.org/10.3390/computation10090157 - 8 Sep 2022
Cited by 2 | Viewed by 2113
Abstract
Processing noise online in sensors-based measurement data (SMD) and mitigating the effect of domain drift are always challenges. As a result, it negatively impacts the effectiveness and feasibility of data-driven model (DDM)-based mechanical-system fault identification (MFI). Here, we propose an online bearing fault [...] Read more.
Processing noise online in sensors-based measurement data (SMD) and mitigating the effect of domain drift are always challenges. As a result, it negatively impacts the effectiveness and feasibility of data-driven model (DDM)-based mechanical-system fault identification (MFI). Here, we propose an online bearing fault diagnosis method named ANFIS-BFDM by using an adaptive neurofuzzy inference system (ANFIS). Reduction in the influence of domain drift between the source domain and target domain (DDSTD) is considered in both the data processing and fault identification. Online solutions for preprocessing SMD and exploiting the filtered data to label the target domain are presented in a fusion domain deriving from the source and target domains. First, in the offline phase, frequency-based splitting of SMD into different time series is performed to cancel the high-frequency region. An optimal data screening threshold (ODST) is distilled in the remaining low-frequency data to develop an impulse noise filter named FIN. An ANFIS then identifies the dynamic response of the bearing(s) via the filtered data. The FIN and ANFIS are finally exploited during the online phase to filter noise and recognize the object’s health status online. The survey results reflect the positive effects of the method, even if severe impulse noise appears in the databases. Full article
(This article belongs to the Special Issue Intelligent Computing, Modeling and its Applications)
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15 pages, 2348 KiB  
Article
Capturing the Complexity of COVID-19 Research: Trend Analysis in the First Two Years of the Pandemic Using a Bayesian Probabilistic Model and Machine Learning Tools
by Javier De La Hoz-M, Susana Mendes, María José Fernández-Gómez and Yolanda González Silva
Computation 2022, 10(9), 156; https://doi.org/10.3390/computation10090156 - 8 Sep 2022
Cited by 2 | Viewed by 2277
Abstract
Publications about COVID-19 have occurred practically since the first outbreak. Therefore, studying the evolution of the scientific publications on COVID-19 can provide us with information on current research trends and can help researchers and policymakers to form a structured view of the existing [...] Read more.
Publications about COVID-19 have occurred practically since the first outbreak. Therefore, studying the evolution of the scientific publications on COVID-19 can provide us with information on current research trends and can help researchers and policymakers to form a structured view of the existing evidence base of COVID-19 and provide new research directions. This growth rate was so impressive that the need for updated information and research tools become essential to mitigate the spread of the virus. Therefore, traditional bibliographic research procedures, such as systematic reviews and meta-analyses, become time-consuming and limited in focus. This study aims to study the scientific literature on COVID-19 that has been published since its inception and to map the evolution of research in the time range between February 2020 and January 2022. The search was carried out in PubMed extracting topics using text mining and latent Dirichlet allocation modeling and a trend analysis was performed to analyze the temporal variations in research for each topic. We also study the distribution of these topics between countries and journals. 126,334 peer-reviewed articles and 16 research topics were identified. The countries with the highest number of scientific publications were the United States of America, China, Italy, United Kingdom, and India, respectively. Regarding the distribution of the number of publications by journal, we found that of the 7040 sources Int. J. Environ. Res. Public Health, PLoS ONE, and Sci. Rep., were the ones that led the publications on COVID-19. We discovered a growing tendency for eight topics (Prevention, Telemedicine, Vaccine immunity, Machine learning, Academic parameters, Risk factors and morbidity and mortality, Information synthesis methods, and Mental health), a falling trend for five of them (Epidemiology, COVID-19 pathology complications, Diagnostic test, Etiopathogenesis, and Political and health factors), and the rest varied throughout time with no discernible patterns (Therapeutics, Pharmacological and therapeutic target, and Repercussion health services). Full article
(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))
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41 pages, 664 KiB  
Article
Credit Spreads, Leverage and Volatility: A Cointegration Approach
by Federico Maglione
Computation 2022, 10(9), 155; https://doi.org/10.3390/computation10090155 - 5 Sep 2022
Cited by 2 | Viewed by 2352
Abstract
This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread [...] Read more.
This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread changes. Using a novel structural model in which equity is modeled as a compound option on the firm’s assets, a new methodology for estimating the unobservable market value of the firm’s assets and volatility is developed. The proposed model allows to significantly reduce the pricing errors in predicting credit spreads when compared with several structural models. In terms of correlation analysis, it is shown that not accounting for the long-run equilibrium equation embedded in an error correction mechanism (ECM) results into a misspecification problem when regressing a set of explanatory variables onto the spread changes. Once credit spreads, leverage and volatility are correctly modeled, thus allowing for a long-run equilibrium, the fit of the regressions sensibly increases if compared to the results of previous research. It is further shown that most of the cross-sectional variation of the spreads appears to be more driven by firm-specific characteristics rather than systematic factors. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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19 pages, 41334 KiB  
Article
3D LiDAR Based SLAM System Evaluation with Low-Cost Real-Time Kinematics GPS Solution
by Stefan Hensel, Marin B. Marinov and Markus Obert
Computation 2022, 10(9), 154; https://doi.org/10.3390/computation10090154 - 4 Sep 2022
Cited by 3 | Viewed by 6910
Abstract
Positioning mobile systems with high accuracy is a prerequisite for intelligent autonomous behavior, both in industrial environments and in field robotics. This paper describes the setup of a robotic platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. [...] Read more.
Positioning mobile systems with high accuracy is a prerequisite for intelligent autonomous behavior, both in industrial environments and in field robotics. This paper describes the setup of a robotic platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. A configuration using a mobile robot Husky A200, and a LiDAR (light detection and ranging) sensor was used to implement the setup. For verification of the proposed setup, different scan matching methods for odometry determination in indoor and outdoor environments are tested. An assessment of the accuracy of the baseline 3D-SLAM system and the selected evaluation system is presented by comparing different scenarios and test situations. It was shown that the hdl_graph_slam in combination with the LiDAR OS1 and the scan matching algorithms FAST_GICP and FAST_VGICP achieves good mapping results with accuracies up to 2 cm. Full article
(This article belongs to the Special Issue Applications of Statistics and Machine Learning in Electronics)
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17 pages, 1911 KiB  
Article
Evaluation of the Effectiveness of Community Activities Restriction in Containing the Spread of COVID-19 in West Java, Indonesia Using Time-Series Clustering
by Dhika Surya Pangestu, Sukono and Nursanti Anggriani
Computation 2022, 10(9), 153; https://doi.org/10.3390/computation10090153 - 4 Sep 2022
Cited by 1 | Viewed by 1892
Abstract
The purpose of this research is to classify time-series data on the number of daily COVID-19 cases based on the dynamics. This research aims to evaluate the effectiveness of community activity restrictions in suppressing the number of new cases of COVID-19 in cities [...] Read more.
The purpose of this research is to classify time-series data on the number of daily COVID-19 cases based on the dynamics. This research aims to evaluate the effectiveness of community activity restrictions in suppressing the number of new cases of COVID-19 in cities and regencies in West Java. We performed time-series clustering on daily positive case data for COVID-19 in 27 cities and regencies in West Java Province, Indonesia for this study. The k-medoids clustering algorithm was used for clustering, with shape-based lock step measures, specifically, the cross correlation-based distance. We used daily new infected cases data for COVID-19 in 27 cities and regencies in West Java Province during the worst situation. We used data from 1 July 2021 to 31 September 2021 and from 1 January 2022 to 31 May 2022, during the Emergency Community Activity Restriction period (PPKM). According to our findings, the optimal number of clusters that could be formed from the data we had was 4 clusters for the first period and 2 clusters for the second period, with silhouette value of 0.2633 and 0.6363, respectively. For the first period, we discovered that PPKM was successful in clusters 1 and 2, namely in 25 cities/districts in West Java, except for Bogor and Depok, while for the second period, we found PPKM to be effective in reducing the number of COVID-19 cases throughout cities and regencies in West Java. This shows there is an improvement from the implementation of PPKM in the first period. We also found that the cluster that was formed was not only influenced by the effectiveness of the PPKM, but also by geography. The closer a city is to a hotspot region for the spread of COVID-19, the earlier the increase in the number of new COVID-19 cases will occur. Full article
(This article belongs to the Special Issue Computation to Fight SARS-CoV-2 (CoVid-19))
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8 pages, 9593 KiB  
Article
The Methods of Three-Dimensional Modeling of the Hydrogenerator Thrust Bearing
by Oleksii Tretiak, Dmitriy Kritskiy, Igor Kobzar, Mariia Arefieva and Viacheslav Nazarenko
Computation 2022, 10(9), 152; https://doi.org/10.3390/computation10090152 - 2 Sep 2022
Cited by 7 | Viewed by 2156
Abstract
In the presented scientific work, the basic design versions of the thrust bearings of Hydrogenerators are considered. The main causes of emergencies in the thrust bearing unit of a high-power Hydrogenerator are considered. The main requirements for the operation of thrust bearings are [...] Read more.
In the presented scientific work, the basic design versions of the thrust bearings of Hydrogenerators are considered. The main causes of emergencies in the thrust bearing unit of a high-power Hydrogenerator are considered. The main requirements for the operation of thrust bearings are submitted. Cause-and-effect relationships of emerging and development of defects are established. Existing methods for calculating the stressed state of a thrust bearing in the classical formulation for a stationary mode of operation are considered. The main features of the operation of the thrust bearing unit are investigated in relation to the features of the sliding bearings. The calculation of the elastic chambers of the hydraulic thrust bearing in a three-dimensional formulation is carried out, taking into account the physical properties of the oil, the material of the chambers and distribution of the acting loads. It is shown that the applied designs of Join Stock Company “Ukrainian Energy Machines” can be used in high-power Hydrogenerators. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)
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14 pages, 1219 KiB  
Article
Approximating Fixed Points of Nonexpansive Type Mappings via General Picard–Mann Algorithm
by Rahul Shukla and Rekha Panicker
Computation 2022, 10(9), 151; https://doi.org/10.3390/computation10090151 - 31 Aug 2022
Cited by 1 | Viewed by 1853
Abstract
The aim of this paper is to approximate fixed points of nonexpansive type mappings in Banach spaces when the set of fixed points is nonempty. We study the general Picard–Mann (GPM) algorithm, obtaining the weak and strong convergence theorems. We provide an example [...] Read more.
The aim of this paper is to approximate fixed points of nonexpansive type mappings in Banach spaces when the set of fixed points is nonempty. We study the general Picard–Mann (GPM) algorithm, obtaining the weak and strong convergence theorems. We provide an example to illustrate the convergence behaviour of the GPM algorithm. We compare the GPM algorithm with other existing (well known) algorithms numerically (under different parameters and initial guesses). Full article
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16 pages, 1946 KiB  
Article
Signal Processing Algorithm for Monopulse Noise Noncoherent Wideband Helicopter Altitude Radar
by Valeriy Volosyuk, Volodymyr Pavlikov, Simeon Zhyla, Eduard Tserne, Oleksii Odokiienko, Andrii Humennyi, Anatoliy Popov and Oleh Uruskiy
Computation 2022, 10(9), 150; https://doi.org/10.3390/computation10090150 - 31 Aug 2022
Cited by 3 | Viewed by 1854
Abstract
Radio altimeters are an important component of modern helicopter on-board systems. These devices currently involve the use of narrowband deterministic signals, that limits their potential technical characteristics. Given the significant breakthrough in the development of wideband and ultra-wideband radio electronics, it is promising [...] Read more.
Radio altimeters are an important component of modern helicopter on-board systems. These devices currently involve the use of narrowband deterministic signals, that limits their potential technical characteristics. Given the significant breakthrough in the development of wideband and ultra-wideband radio electronics, it is promising to create on-board radio complexes capable of obtaining the necessary information using wideband stochastic signals. At the same time, when developing such complexes, it is important to use optimal synthesis methods for radio systems, which will allow optimal signal processing algorithms and potential accuracy parameters to be obtained. In this work, the algorithm to measure flight altitude for a helicopter or an unmanned aerial vehicle based on the processing of wideband and ultra-wideband pulsed stochastic signals is synthesized for the first time by the maximum-likelihood method. When formulating the problem, the mathematical model of the signal and observation is specified, and their statistical characteristics are investigated. The peculiarity of the synthesis task is the use of a noise pulse transmitter, which implements the function of an underlying surface illuminator, as well as considering the signal structure destruction during its radiation, propagation, and reflection. This signal shape destruction makes it impossible to synthesize a radar with internally coherent processing when working on one receiving antenna. In accordance with the synthesized algorithm, a simulation model of a pulsed radar with a stochastic probing signal has been developed and the results of its modeling are presented. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering – Synergetic Engineering)
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10 pages, 252 KiB  
Communication
Spillover Effects in Empirical Corporate Finance: Choosing the Proxy for Treatment Coverage
by Fabiana Gómez and David Pacini
Computation 2022, 10(9), 149; https://doi.org/10.3390/computation10090149 - 31 Aug 2022
Viewed by 2081
Abstract
The existing literature indicates that spillovers can lead to a complicated bias in the estimation of causal effects in empirical corporate finance. We show that, under the assumption of simple random treatment assignment and when the proxy chosen for the group-level treatment coverage [...] Read more.
The existing literature indicates that spillovers can lead to a complicated bias in the estimation of causal effects in empirical corporate finance. We show that, under the assumption of simple random treatment assignment and when the proxy chosen for the group-level treatment coverage is the leave-one-out average treatment, such a spillover bias exists if and only if the average indirect effects on the treated and untreated groups are different. We quantify the gains in spillover bias reduction using Monte Carlo exercises. We propose a Wald test to statistically infer the presence of bias. We illustrate the application of this test to bear out spillovers in firms’ employment decisions. Full article
(This article belongs to the Special Issue Causal Inference, Probability Theory and Graphical Concepts)
20 pages, 2575 KiB  
Article
Face Detection & Recognition from Images & Videos Based on CNN & Raspberry Pi
by Muhammad Zamir, Nouman Ali, Amad Naseem, Areeb Ahmed Frasteen, Bushra Zafar, Muhammad Assam, Mahmoud Othman and El-Awady Attia
Computation 2022, 10(9), 148; https://doi.org/10.3390/computation10090148 - 30 Aug 2022
Cited by 25 | Viewed by 10085
Abstract
The amount of multimedia content is growing exponentially and a major portion of multimedia content uses images and video. Researchers in the computer vision community are exploring the possible directions to enhance the system accuracy and reliability, and these are the main requirements [...] Read more.
The amount of multimedia content is growing exponentially and a major portion of multimedia content uses images and video. Researchers in the computer vision community are exploring the possible directions to enhance the system accuracy and reliability, and these are the main requirements for robot vision-based systems. Due to the change of facial expressions and the wearing of masks or sunglasses, many face recognition systems fail or the accuracy in recognizing the face decreases in these scenarios. In this work, we contribute a real time surveillance framework using Raspberry Pi and CNN (Convolutional Neural Network) for facial recognition. We have provided a labeled dataset to the system. First, the system is trained upon the labeled dataset to extract different features of the face and landmark face detection and then it compares the query image with the dataset on the basis of features and landmark face detection. Finally, it compares faces and votes between them and gives a result that is based on voting. The classification accuracy of the system based on the CNN model is compared with a mid-level feature extractor that is Histogram of Oriented Gradient (HOG) and the state-of-the-art face detection and recognition methods. Moreover, the accuracy in recognizing the faces in the cases of wearing a mask or sunglasses or in live videos is also evaluated. The highest accuracy achieved for the VMU, face recognition, and 14 celebrity datasets is 98%, 98.24%, 89.39%, and 95.71%, respectively. Experimental results on standard image benchmarks demonstrate the effectiveness of the proposed research in accurate face recognition compared to the state-of-the-art face detection and recognition methods. Full article
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20 pages, 50877 KiB  
Article
Numerical Computation-Based Position Estimation for QR Code Object Marker: Mathematical Model and Simulation
by Mooi Khee Teoh, Kenneth T. K. Teo and Hou Pin Yoong
Computation 2022, 10(9), 147; https://doi.org/10.3390/computation10090147 - 26 Aug 2022
Cited by 4 | Viewed by 2970
Abstract
Providing position and orientation estimations from a two-dimensional (2D) image is challenging, as such images lack depth information between the target and the automation system. This paper proposes a numerical-based monocular positioning method to determine the position and orientation of a single quick [...] Read more.
Providing position and orientation estimations from a two-dimensional (2D) image is challenging, as such images lack depth information between the target and the automation system. This paper proposes a numerical-based monocular positioning method to determine the position and orientation of a single quick response (QR) code object marker. The three-dimensional (3D) positional information can be extracted from the underdetermined system using the QR code’s four vertices as positioning points. This method uses the fundamental principles of the pinhole imaging theory and similar triangular rules to correspond the QR code’s corner points in a 3D environment to the 2D image. The numerical-based model developed with suitable guessing parameters and correct updating rules successfully determines the QR code marker’s position. At the same time, an inversed rotation matrix determines the QR code marker’s orientation. Then, the MATLAB platform simulates the proposed positioning model to identify the maximum rotation angles detectable at various locations using a single QR code image with the known QR code’s size and the camera’s focal length. The simulation results show that the proposed numerical model can measure the position and orientation of the tilted QR code marker within 30 iterations with great accuracy. Additionally, it can achieve no more than a two-degree angle calculation error and less than a five millimeter distance difference. Overall, more than 77.28% of the coordinate plane simulated shows a converged result. The simulation results are verified using the input value, and the method is also capable of experimental verification using a monocular camera system and QR code as the landmark. Full article
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25 pages, 11453 KiB  
Article
Computational Assessment of Xanthones from African Medicinal Plants as Aldose Reductase Inhibitors
by Onikepe Deborah Owoseeni, Rajesh B. Patil, Prajakta M. Phage, Ruth Mosunmola Ogboye, Marcus Durojaye Ayoola, Samson Oluwaseyi Famuyiwa, Felix Olusegun Gboyero, Derek Tantoh Ndinteh and Kolade Olatubosun Faloye
Computation 2022, 10(9), 146; https://doi.org/10.3390/computation10090146 - 26 Aug 2022
Cited by 10 | Viewed by 2293
Abstract
Diabetes mellitus is a life-threatening non-communicable disease that affects all age groups. Despite the increased attention it has received in recent years, the number of diabetic patients has grown exponentially. These increased cases are attributed to essential enzymes involved in blood glucose regulation. [...] Read more.
Diabetes mellitus is a life-threatening non-communicable disease that affects all age groups. Despite the increased attention it has received in recent years, the number of diabetic patients has grown exponentially. These increased cases are attributed to essential enzymes involved in blood glucose regulation. In this study, we attempt to reveal the aldose reductase inhibitory potential of xanthones isolated from African medicinal plants. Ensemble docking, molecular dynamics simulation, density functional theory (DFT), and ADMET methods were employed to identify drug candidates as aldose reductase inhibitors. The ensemble docking results identified mangostenone B, bangangxanthone A, smeathxanthone B, mangostenone A, and allanxanthone B as potent inhibitors against the aldose reductase enzyme. Molecular dynamics studies showed the xanthones established better binding mode and affinities against the enzyme. Moreover, the electronic properties of the xanthones explained their good pharmacological potentials. Therefore, our findings suggest that the hit molecules be investigated in vitro and in vivo for drug development against aldose reductase. Full article
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19 pages, 4614 KiB  
Article
Machine Learning and Rules Induction in Support of Analog Amplifier Design
by Malinka Ivanova and Miona Andrejević Stošović
Computation 2022, 10(9), 145; https://doi.org/10.3390/computation10090145 - 25 Aug 2022
Cited by 2 | Viewed by 2144
Abstract
The aim of the paper is to present a two-step method for facilitating the design of analog amplifiers taking into account the bottom–top approach and utilizing machine learning techniques. The X-chart and a framework describing the specificity of analog circuit design using machine [...] Read more.
The aim of the paper is to present a two-step method for facilitating the design of analog amplifiers taking into account the bottom–top approach and utilizing machine learning techniques. The X-chart and a framework describing the specificity of analog circuit design using machine learning are introduced. The possibility of libraries with open machine learning models to support the designer is also discussed. The proposed method is verified for a three-stage amplifier design. In the first step, the stage type is predicted with 89.74% accuracy as the applied learner is a Decision Tree machine learning algorithm. Moreover, two induction rule algorithms are used for predictive logic generation. In the second step, some typical parameters for a given stage are predicted considering four learners: Decision Tree, Random Forest, Gradient Boosted Trees, and Support Vector Machine. The most suitable is found to be Support Vector Machine, which is characterized with the smallest obtained errors. Full article
(This article belongs to the Special Issue Applications of Statistics and Machine Learning in Electronics)
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19 pages, 2494 KiB  
Article
A Review and Taxonomy on Fault Analysis in Transmission Power Systems
by Yaser Al Mtawa, Anwar Haque and Talal Halabi
Computation 2022, 10(9), 144; https://doi.org/10.3390/computation10090144 - 24 Aug 2022
Cited by 8 | Viewed by 4440
Abstract
Enhancing resiliency in a power grid system is one of the core mandates of electrical distribution companies to provide high-level service. The power resiliency research community has proposed numerous schemes, to detect, classify, and localize fault events. However, the literature still lacks a [...] Read more.
Enhancing resiliency in a power grid system is one of the core mandates of electrical distribution companies to provide high-level service. The power resiliency research community has proposed numerous schemes, to detect, classify, and localize fault events. However, the literature still lacks a comprehensive taxonomy of these schemes which can help advance future research. This study aims to provide a compact yet comprehensive review of the state-of-the-art solutions to fault analysis in transmission power systems. We discuss fault types and several fault-analysis methodologies adopted by relevant research works, propose a novel framework to classify these works, and highlight their strengths and limitations. We anticipate that this brief review would be helpful as a literature review and benefit the research community in choosing suitable techniques for fault analysis. Full article
(This article belongs to the Section Computational Engineering)
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13 pages, 3530 KiB  
Article
Modeling of 2R Planar Dumbbell Stacker Robot Locomotion Using Force Control for Gripper Dexterous Manipulation
by Sergei Kondratev and Victor Meshcheryakov
Computation 2022, 10(9), 143; https://doi.org/10.3390/computation10090143 - 23 Aug 2022
Cited by 3 | Viewed by 2563
Abstract
This paper describes a novel approach to the robotic system’s dexterous manipulator arm design. A simulation model of the robotic system is developed in the MATLAB/Simulink environment. The designed gripper moves the dumbbells from one shelf to another using impedance and dynamics control. [...] Read more.
This paper describes a novel approach to the robotic system’s dexterous manipulator arm design. A simulation model of the robotic system is developed in the MATLAB/Simulink environment. The designed gripper moves the dumbbells from one shelf to another using impedance and dynamics control. The novel approach to contact force control was tested. For the most accurate simulation, the size and mass parameters of the manipulator and dumbbells are determined. In addition, various force parameters such as normal, friction and damping were evaluated. The dynamic behavior of the robotic system was described by the Lagrange dynamics equations to find the acceleration of the robot’s joints during friction interaction, and the energy performance was described. The corresponding dynamic model and its analysis are the starting point for its successful solution. The analytical and numerical descriptions are obtained and can be further used for computer simulation of the system, calculation of dynamic constraints, optimization of manipulator design, synthesis of trajectory planner and motion control algorithms of dexterous manipulative robotic systems. Full article
(This article belongs to the Special Issue Control Systems, Mathematical Modeling and Automation)
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