Pub Date : 2023-10-04DOI: 10.3390/computation11100198
M. Mohamed, S. M. Mabrouk, A. S. Rashed
In recent times, the global community has been faced with the unprecedented challenge of the coronavirus disease (COVID-19) pandemic, which has had a profound and enduring impact on both global health and the global economy. The utilization of mathematical modeling has become an essential instrument in the characterization and understanding of the dynamics associated with infectious illnesses. In this study, the utilization of the differential quadrature method (DQM) was employed in order to anticipate the characterization of the dynamics of COVID-19 through a fractional mathematical model. Uniform and non-uniform polynomial differential quadrature methods (PDQMs) and a discrete singular convolution method (DSCDQM) were employed in the examination of the dynamics of COVID-19 in vulnerable, exposed, deceased, asymptomatic, and recovered persons. An analysis was conducted to compare the methodologies used in this study, as well as the modified Euler method, in order to highlight the superior efficiency of the DQM approach in terms of code-execution times. The results demonstrated that the fractional order significantly influenced the outcomes. As the fractional order tended towards unity, the anticipated numbers of vulnerable, exposed, deceased, asymptomatic, and recovered individuals increased. During the initial week of the inquiry, there was a substantial rise in the number of individuals who contracted COVID-19, which was primarily attributed to the disease’s high transmission rate. As a result, there was an increase in the number of individuals who recovered, in tandem with the rise in the number of infected individuals. These results highlight the importance of the fractional order in influencing the dynamics of COVID-19. The utilization of the DQM approach, characterized by its proficient code-execution durations, provided significant insights into the dynamics of COVID-19 among diverse population cohorts and enhanced our comprehension of the evolution of the pandemic. The proposed method was efficient in dealing with ordinary differential equations (ODEs), partial differential equations (PDEs), and fractional differential equations (FDEs), in either linear or nonlinear forms. In addition, the stability of the DQM and its validity were verified during the present study. Moreover, the error analysis showed that DQM has better error percentages in many applications than other relevant techniques.
{"title":"Mathematical Investigation of the Infection Dynamics of COVID-19 Using the Fractional Differential Quadrature Method","authors":"M. Mohamed, S. M. Mabrouk, A. S. Rashed","doi":"10.3390/computation11100198","DOIUrl":"https://doi.org/10.3390/computation11100198","url":null,"abstract":"In recent times, the global community has been faced with the unprecedented challenge of the coronavirus disease (COVID-19) pandemic, which has had a profound and enduring impact on both global health and the global economy. The utilization of mathematical modeling has become an essential instrument in the characterization and understanding of the dynamics associated with infectious illnesses. In this study, the utilization of the differential quadrature method (DQM) was employed in order to anticipate the characterization of the dynamics of COVID-19 through a fractional mathematical model. Uniform and non-uniform polynomial differential quadrature methods (PDQMs) and a discrete singular convolution method (DSCDQM) were employed in the examination of the dynamics of COVID-19 in vulnerable, exposed, deceased, asymptomatic, and recovered persons. An analysis was conducted to compare the methodologies used in this study, as well as the modified Euler method, in order to highlight the superior efficiency of the DQM approach in terms of code-execution times. The results demonstrated that the fractional order significantly influenced the outcomes. As the fractional order tended towards unity, the anticipated numbers of vulnerable, exposed, deceased, asymptomatic, and recovered individuals increased. During the initial week of the inquiry, there was a substantial rise in the number of individuals who contracted COVID-19, which was primarily attributed to the disease’s high transmission rate. As a result, there was an increase in the number of individuals who recovered, in tandem with the rise in the number of infected individuals. These results highlight the importance of the fractional order in influencing the dynamics of COVID-19. The utilization of the DQM approach, characterized by its proficient code-execution durations, provided significant insights into the dynamics of COVID-19 among diverse population cohorts and enhanced our comprehension of the evolution of the pandemic. The proposed method was efficient in dealing with ordinary differential equations (ODEs), partial differential equations (PDEs), and fractional differential equations (FDEs), in either linear or nonlinear forms. In addition, the stability of the DQM and its validity were verified during the present study. Moreover, the error analysis showed that DQM has better error percentages in many applications than other relevant techniques.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135590605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-03DOI: 10.3390/computation11100197
Adnan Shahriar, Arsalan Majlesi, Arturo Montoya
This paper presents a general procedure to formulate and implement 3D elements of arbitrary order in meshes with multiple element types. This procedure includes obtaining shape functions and integration quadrature and establishing an approach for checking the generated element’s compatibility with adjacent elements’ surfaces. This procedure was implemented in Matlab, using its symbolic and graphics toolbox, and complied as a GUI interface named ShapeGen3D to provide finite element users with a tool to tailor elements according to their analysis needs. ShapeGen3D also outputs files with the element formulation needed to enable users to implement the generated elements in other programming languages or through user elements in commercial finite element software. Currently, finite element (FE) users are limited to employing element formulation available in the literature, commercial software, or existing element libraries. Thus, the developed procedure implemented in ShapeGen3D offers FEM users the possibility to employ elements beyond those readily available. The procedure was tested by generating the formulation for a brick element, a brick transition element, and higher-order hexahedron and tetrahedron elements that can be used in a spectral finite element analysis. The formulation obtained for the 20-node element was in perfect agreement with the formulation available in the literature. In addition, the results showed that the interpolation condition was met for all the generated elements, which provides confidence in the implementation of the process. Researchers and educators can use this procedure to efficiently develop and illustrate three-dimensional elements.
{"title":"A General Procedure to Formulate 3D Elements for Finite Element Applications","authors":"Adnan Shahriar, Arsalan Majlesi, Arturo Montoya","doi":"10.3390/computation11100197","DOIUrl":"https://doi.org/10.3390/computation11100197","url":null,"abstract":"This paper presents a general procedure to formulate and implement 3D elements of arbitrary order in meshes with multiple element types. This procedure includes obtaining shape functions and integration quadrature and establishing an approach for checking the generated element’s compatibility with adjacent elements’ surfaces. This procedure was implemented in Matlab, using its symbolic and graphics toolbox, and complied as a GUI interface named ShapeGen3D to provide finite element users with a tool to tailor elements according to their analysis needs. ShapeGen3D also outputs files with the element formulation needed to enable users to implement the generated elements in other programming languages or through user elements in commercial finite element software. Currently, finite element (FE) users are limited to employing element formulation available in the literature, commercial software, or existing element libraries. Thus, the developed procedure implemented in ShapeGen3D offers FEM users the possibility to employ elements beyond those readily available. The procedure was tested by generating the formulation for a brick element, a brick transition element, and higher-order hexahedron and tetrahedron elements that can be used in a spectral finite element analysis. The formulation obtained for the 20-node element was in perfect agreement with the formulation available in the literature. In addition, the results showed that the interpolation condition was met for all the generated elements, which provides confidence in the implementation of the process. Researchers and educators can use this procedure to efficiently develop and illustrate three-dimensional elements.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135697621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-03DOI: 10.3390/computation11100196
Sunil Chamoli, Amit Joshi, Sumit Rana, Suvanjan Bhattacharaya, Ashutosh Gupta, Siddharth Ghansela, Chinaruk Thianpong, Smith Eiamsa-ard
After publishing a research article in the year 2019, a cam-shaped cylinder was introduced, and the results expressed its ability to prevent the vortex from shedding. This makes the cam-shaped cylinder a better performer than the circular cylinder. This work is an extension of past work with the aim of further reducing drag by attaching a backward splitter plate to a cam-shaped cylinder. In an attempt to decrease drag and regulate the wake regime more efficiently than the traditional splitter plate control devices, a splitter plate flow departure control device is presented in this paper for a low Reynolds number flow range (Re = 50–200). It has been noted that when plate length increases, integral parameters like drag, lift, and Strouhal number do not change monotonically. The Strouhal number (St) increases with a drop in D2/Deq, but the average drag reduces with a rise in Re and a decrease in D2/Deq, respectively. In terms of decreased drag, the current cam-shaped cylinders attached to a rearward splitter plate have shown their superiority to other bluff bodies.
{"title":"Numerical Methodology to Reduce the Drag and Control Flow around a Cam-Shaped Cylinder Integrated with Backward Splitter Plate","authors":"Sunil Chamoli, Amit Joshi, Sumit Rana, Suvanjan Bhattacharaya, Ashutosh Gupta, Siddharth Ghansela, Chinaruk Thianpong, Smith Eiamsa-ard","doi":"10.3390/computation11100196","DOIUrl":"https://doi.org/10.3390/computation11100196","url":null,"abstract":"After publishing a research article in the year 2019, a cam-shaped cylinder was introduced, and the results expressed its ability to prevent the vortex from shedding. This makes the cam-shaped cylinder a better performer than the circular cylinder. This work is an extension of past work with the aim of further reducing drag by attaching a backward splitter plate to a cam-shaped cylinder. In an attempt to decrease drag and regulate the wake regime more efficiently than the traditional splitter plate control devices, a splitter plate flow departure control device is presented in this paper for a low Reynolds number flow range (Re = 50–200). It has been noted that when plate length increases, integral parameters like drag, lift, and Strouhal number do not change monotonically. The Strouhal number (St) increases with a drop in D2/Deq, but the average drag reduces with a rise in Re and a decrease in D2/Deq, respectively. In terms of decreased drag, the current cam-shaped cylinders attached to a rearward splitter plate have shown their superiority to other bluff bodies.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135697022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cervical cancer poses a significant global health burden, affecting women worldwide. Timely and accurate detection is crucial for effective treatment and improved patient outcomes. The Pap smear test has long been a standard cytology screening method, enabling early cancer diagnosis. However, to enhance quantitative analysis and refine diagnostic capabilities, precise segmentation of the cervical cytoplasm and nucleus using deep learning techniques holds immense promise. This research focuses on addressing the primary challenge of achieving accurate segmentation in the presence of noisy data commonly encountered in Pap smear images. Poisson noise, a prevalent type of noise, corrupts these images, impairing the precise delineation of the cytoplasm and nucleus. Consequently, segmentation boundaries become indistinct, leading to compromised overall accuracy. To overcome these limitations, the utilization of U-Net, a deep learning architecture specifically designed for automatic segmentation, has been proposed. This approach aims to mitigate the adverse effects of Poisson noise on the digitized Pap smear slides. The evaluation of the proposed methodology involved a dataset of 110 Pap smear slides. The experimental results demonstrate that the proposed approach successfully achieves precise segmentation of the nucleus and cytoplasm in noise-free images. By preserving the boundaries of both cellular components, the method facilitates accurate feature extraction, thus contributing to improved diagnostic capabilities. Comparative analysis between noisy and noise-free images reveals the superiority of the presented approach in terms of segmentation accuracy, as measured by various metrics, including the Dice coefficient, specificity, sensitivity, and intersection over union (IoU). The findings of this study underline the potential of deep-learning-based segmentation techniques to enhance cervical cancer diagnosis and pave the way for improved quantitative analysis in this critical field of women’s health.
{"title":"A Robust Deep Learning Approach for Accurate Segmentation of Cytoplasm and Nucleus in Noisy Pap Smear Images","authors":"Nahida Nazir, Abid Sarwar, Baljit Singh Saini, Rafeeya Shams","doi":"10.3390/computation11100195","DOIUrl":"https://doi.org/10.3390/computation11100195","url":null,"abstract":"Cervical cancer poses a significant global health burden, affecting women worldwide. Timely and accurate detection is crucial for effective treatment and improved patient outcomes. The Pap smear test has long been a standard cytology screening method, enabling early cancer diagnosis. However, to enhance quantitative analysis and refine diagnostic capabilities, precise segmentation of the cervical cytoplasm and nucleus using deep learning techniques holds immense promise. This research focuses on addressing the primary challenge of achieving accurate segmentation in the presence of noisy data commonly encountered in Pap smear images. Poisson noise, a prevalent type of noise, corrupts these images, impairing the precise delineation of the cytoplasm and nucleus. Consequently, segmentation boundaries become indistinct, leading to compromised overall accuracy. To overcome these limitations, the utilization of U-Net, a deep learning architecture specifically designed for automatic segmentation, has been proposed. This approach aims to mitigate the adverse effects of Poisson noise on the digitized Pap smear slides. The evaluation of the proposed methodology involved a dataset of 110 Pap smear slides. The experimental results demonstrate that the proposed approach successfully achieves precise segmentation of the nucleus and cytoplasm in noise-free images. By preserving the boundaries of both cellular components, the method facilitates accurate feature extraction, thus contributing to improved diagnostic capabilities. Comparative analysis between noisy and noise-free images reveals the superiority of the presented approach in terms of segmentation accuracy, as measured by various metrics, including the Dice coefficient, specificity, sensitivity, and intersection over union (IoU). The findings of this study underline the potential of deep-learning-based segmentation techniques to enhance cervical cancer diagnosis and pave the way for improved quantitative analysis in this critical field of women’s health.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135696284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.3390/computation11100193
Pavel V. Zakharov, Elena A. Korznikova, Artem A. Izosimov, Andrey S. Kochkin
This study examines the mechanism of nonlinear supratransmission (NST), which involves the transfer of disturbance to discrete media at frequencies not supported by the structure. We considered a model crystal with A3B stoichiometry. The investigation was carried out using atomistic modeling through molecular dynamics. The interatomic interaction was determined by a potential obtained through the embedded atom method, which approximates the properties of the Pt3Al crystal. The effect of NST is an important property of many discrete structures. Its existence requires the discreteness and nonlinearity of the medium, as well as the presence of a forbidden zone in its spectrum. This work focuses on the differences in the NST effect due to the anisotropy of crystallographic directions. Three planes along which the disturbance caused by NST propagated were considered: (100), (110), and (111). It was found that the intensity of the disturbance along the (100) plane is an order of magnitude lower than for more densely packed directions. Differences in the shape of solitary waves depending on the propagation direction were shown. Moreover, all waves can be described by a single equation, being a solution of the discrete variational equations of macroscopic and microscopic displacements, with different parameters, emphasizing the unified nature of the waves and the contribution of crystal anisotropy to their properties. Studying the NST phenomenon is essential due to numerous applications of the latter, such as implications in information transmission and signal processing. Understanding how disturbances propagate in discrete media could lead to advancements in communication technologies, data storage, and signal amplification where the earlier mentioned ability to describe it with analytical equations is of particular importance.
{"title":"The Influence of Crystal Anisotropy on the Characteristics of Solitary Waves in the Nonlinear Supratransmission Effect: Molecular Dynamic Modeling","authors":"Pavel V. Zakharov, Elena A. Korznikova, Artem A. Izosimov, Andrey S. Kochkin","doi":"10.3390/computation11100193","DOIUrl":"https://doi.org/10.3390/computation11100193","url":null,"abstract":"This study examines the mechanism of nonlinear supratransmission (NST), which involves the transfer of disturbance to discrete media at frequencies not supported by the structure. We considered a model crystal with A3B stoichiometry. The investigation was carried out using atomistic modeling through molecular dynamics. The interatomic interaction was determined by a potential obtained through the embedded atom method, which approximates the properties of the Pt3Al crystal. The effect of NST is an important property of many discrete structures. Its existence requires the discreteness and nonlinearity of the medium, as well as the presence of a forbidden zone in its spectrum. This work focuses on the differences in the NST effect due to the anisotropy of crystallographic directions. Three planes along which the disturbance caused by NST propagated were considered: (100), (110), and (111). It was found that the intensity of the disturbance along the (100) plane is an order of magnitude lower than for more densely packed directions. Differences in the shape of solitary waves depending on the propagation direction were shown. Moreover, all waves can be described by a single equation, being a solution of the discrete variational equations of macroscopic and microscopic displacements, with different parameters, emphasizing the unified nature of the waves and the contribution of crystal anisotropy to their properties. Studying the NST phenomenon is essential due to numerous applications of the latter, such as implications in information transmission and signal processing. Understanding how disturbances propagate in discrete media could lead to advancements in communication technologies, data storage, and signal amplification where the earlier mentioned ability to describe it with analytical equations is of particular importance.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135895708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.3390/computation11100194
Andrey Lavrenov, Elena Tolkacheva, Sergei Pozdniakov
The computational capabilities of computer tools expand the student’s search capabilities. Conducting computational experiments in the classroom is no longer an organizational problem. This raises the “black box” problem, when the student perceives the computational module as a magician’s box and loses conceptual control over the computational process. This article analyses the use of various computer tools, both existing and specially created for “key” computational experiments, that aim at revealing the essential aspects of the introduced concepts using specific examples. This article deals with a number of topics of algebra and calculus that are transitional from school to university, and it shows how computational experiments in the form of a “transparent” box can be used.
{"title":"Computational “Accompaniment” of the Introduction of New Mathematical Concepts","authors":"Andrey Lavrenov, Elena Tolkacheva, Sergei Pozdniakov","doi":"10.3390/computation11100194","DOIUrl":"https://doi.org/10.3390/computation11100194","url":null,"abstract":"The computational capabilities of computer tools expand the student’s search capabilities. Conducting computational experiments in the classroom is no longer an organizational problem. This raises the “black box” problem, when the student perceives the computational module as a magician’s box and loses conceptual control over the computational process. This article analyses the use of various computer tools, both existing and specially created for “key” computational experiments, that aim at revealing the essential aspects of the introduced concepts using specific examples. This article deals with a number of topics of algebra and calculus that are transitional from school to university, and it shows how computational experiments in the form of a “transparent” box can be used.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135828875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.3390/computation11100192
Amany Khalil, Anas M. Hosney Lila, Nouran Ashraf
The climate change crisis has resulted in the need to use sustainable methods in architectural design, including building form and orientation decisions that can save a significant amount of energy consumed by a building. Several previous studies have optimized building form and envelope for energy performance, but the isolated effect of varieties of possible architectural forms for a specific climate has not been fully investigated. This paper proposes four novel office building form generation methods (the polygon that varies between pentagon and decagon; the pixels that are complex cubic forms; the letters including H, L, U, T; cross and complex cubic forms; and the round family including circular and oval forms) and evaluates their annual thermal energy use intensity (EUI) for Cairo (hot climate). Results demonstrated the applicability of the proposed methods in enhancing the energy performance of the new forms in comparison to the base case. The results of the optimizations are compared together, and the four families are discussed in reference to their different architectural aspects and performance. Scatterplots are developed for the round family (highest performance) to test the impact of each dynamic parameter on EUI. The round family optimization process takes a noticeably high calculation time in comparison to other families. Therefore, an Artificial Neural Network (ANN) prediction model is developed for the round family after simulating 1726 iterations. Training of 1200 configurations is used to predict annual EUI for the remaining 526 iterations. The ANN predicted values are compared against the trained to determine the time saved and accuracy.
{"title":"Optimization and Prediction of Different Building Forms for Thermal Energy Performance in the Hot Climate of Cairo Using Genetic Algorithm and Machine Learning","authors":"Amany Khalil, Anas M. Hosney Lila, Nouran Ashraf","doi":"10.3390/computation11100192","DOIUrl":"https://doi.org/10.3390/computation11100192","url":null,"abstract":"The climate change crisis has resulted in the need to use sustainable methods in architectural design, including building form and orientation decisions that can save a significant amount of energy consumed by a building. Several previous studies have optimized building form and envelope for energy performance, but the isolated effect of varieties of possible architectural forms for a specific climate has not been fully investigated. This paper proposes four novel office building form generation methods (the polygon that varies between pentagon and decagon; the pixels that are complex cubic forms; the letters including H, L, U, T; cross and complex cubic forms; and the round family including circular and oval forms) and evaluates their annual thermal energy use intensity (EUI) for Cairo (hot climate). Results demonstrated the applicability of the proposed methods in enhancing the energy performance of the new forms in comparison to the base case. The results of the optimizations are compared together, and the four families are discussed in reference to their different architectural aspects and performance. Scatterplots are developed for the round family (highest performance) to test the impact of each dynamic parameter on EUI. The round family optimization process takes a noticeably high calculation time in comparison to other families. Therefore, an Artificial Neural Network (ANN) prediction model is developed for the round family after simulating 1726 iterations. Training of 1200 configurations is used to predict annual EUI for the remaining 526 iterations. The ANN predicted values are compared against the trained to determine the time saved and accuracy.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135835749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.3390/computation11100191
Barbara Cardone, Ferdinando Di Martino, Salvatore Sessa
This research proposes a new image compression method based on the F1-transform which improves the quality of the reconstructed image without increasing the coding/decoding CPU time. The advantage of compressing color images in the YUV space is due to the fact that while the three bands Red, Green and Blue are equally perceived by the human eye, in YUV space most of the image information perceived by the human eye is contained in the Y band, as opposed to the U and V bands. Using this advantage, we construct a new color image compression algorithm based on F1-transform in which the image compression is accomplished in the YUV space, so that better-quality compressed images can be obtained without increasing the execution time. The results of tests performed on a set of color images show that our color image compression method improves the quality of the decoded images with respect to the image compression algorithms JPEG, F1-transform on the RGB color space and F-transform on the YUV color space, regardless of the selected compression rate and with comparable CPU times.
{"title":"Fuzzy Transform Image Compression in the YUV Space","authors":"Barbara Cardone, Ferdinando Di Martino, Salvatore Sessa","doi":"10.3390/computation11100191","DOIUrl":"https://doi.org/10.3390/computation11100191","url":null,"abstract":"This research proposes a new image compression method based on the F1-transform which improves the quality of the reconstructed image without increasing the coding/decoding CPU time. The advantage of compressing color images in the YUV space is due to the fact that while the three bands Red, Green and Blue are equally perceived by the human eye, in YUV space most of the image information perceived by the human eye is contained in the Y band, as opposed to the U and V bands. Using this advantage, we construct a new color image compression algorithm based on F1-transform in which the image compression is accomplished in the YUV space, so that better-quality compressed images can be obtained without increasing the execution time. The results of tests performed on a set of color images show that our color image compression method improves the quality of the decoded images with respect to the image compression algorithms JPEG, F1-transform on the RGB color space and F-transform on the YUV color space, regardless of the selected compression rate and with comparable CPU times.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135406629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.3390/computation11100188
Kayhan Erciyes
Biological networks such as protein interaction networks, gene regulation networks, and metabolic pathways are examples of complex networks that are large graphs with small-world and scale-free properties. An analysis of these networks has a profound effect on our understanding the origins of life, health, and the disease states of organisms, and it allows for the diagnosis of diseases to aid in the search for remedial processes. In this review, we describe the main analysis methods of biological networks using graph theory, by first defining the main parameters, such as clustering coefficient, modularity, and centrality. We then survey fundamental graph clustering methods and algorithms, followed by the network motif search algorithms, with the aim of finding repeating subgraphs in a biological network graph. A frequently appearing subgraph usually conveys a basic function that is carried out by that small network, and discovering such a function provides an insight into the overall function of the organism. Lastly, we review network alignment algorithms that find similarities between two or more graphs representing biological networks. A conserved subgraph between the biological networks of organisms may mean a common ancestor, and finding such a relationship may help researchers to derive ancestral relationships and to predict the future evolution of organisms to enable the design of new drugs. We provide a review of the research studies in all of these methods, and conclude using the current challenging areas of biological network analysis, and by using graph theory and parallel processing for high performance analysis.
{"title":"Graph-Theoretical Analysis of Biological Networks: A Survey","authors":"Kayhan Erciyes","doi":"10.3390/computation11100188","DOIUrl":"https://doi.org/10.3390/computation11100188","url":null,"abstract":"Biological networks such as protein interaction networks, gene regulation networks, and metabolic pathways are examples of complex networks that are large graphs with small-world and scale-free properties. An analysis of these networks has a profound effect on our understanding the origins of life, health, and the disease states of organisms, and it allows for the diagnosis of diseases to aid in the search for remedial processes. In this review, we describe the main analysis methods of biological networks using graph theory, by first defining the main parameters, such as clustering coefficient, modularity, and centrality. We then survey fundamental graph clustering methods and algorithms, followed by the network motif search algorithms, with the aim of finding repeating subgraphs in a biological network graph. A frequently appearing subgraph usually conveys a basic function that is carried out by that small network, and discovering such a function provides an insight into the overall function of the organism. Lastly, we review network alignment algorithms that find similarities between two or more graphs representing biological networks. A conserved subgraph between the biological networks of organisms may mean a common ancestor, and finding such a relationship may help researchers to derive ancestral relationships and to predict the future evolution of organisms to enable the design of new drugs. We provide a review of the research studies in all of these methods, and conclude using the current challenging areas of biological network analysis, and by using graph theory and parallel processing for high performance analysis.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136343782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.3390/computation11100189
Narendra Kumar, Amit K. Verma, Ravi P. Agarwal
In this paper, we introduce a novel approach employing two-dimensional uniform and non-uniform Haar wavelet collocation methods to effectively solve the generalized Burgers–Huxley and Burgers–Fisher equations. The demonstrated method exhibits an impressive quartic convergence rate. Several test problems are presented to exemplify the accuracy and efficiency of this proposed approach. Our results exhibit exceptional accuracy even with a minimal number of spatial divisions. Additionally, we conduct a comparative analysis of our results with existing methods.
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