In this paper, we prove the existence and regularity of weak solutions for a class of nonlinear elliptic equations with degenerate coercivity and singular lower-order terms with natural growth with respect to the gradient and Lm(⋅) (m(x)≥1) data. The functional setting involves Lebesgue–Sobolev spaces with variable exponents.
{"title":"Degenerate elliptic problem with singular gradient lower order term and variable exponents","authors":"M. A. Zouatini, F. Mokhtari, H. Khelifi","doi":"10.23939/mmc2023.01.133","DOIUrl":"https://doi.org/10.23939/mmc2023.01.133","url":null,"abstract":"In this paper, we prove the existence and regularity of weak solutions for a class of nonlinear elliptic equations with degenerate coercivity and singular lower-order terms with natural growth with respect to the gradient and Lm(⋅) (m(x)≥1) data. The functional setting involves Lebesgue–Sobolev spaces with variable exponents.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135127103","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}
Pedestrian segmentation is a critical task in computer vision, but it can be challenging for segmentation models to accurately classify pedestrians in images with challenging backgrounds and luminosity changes, as well as occlusions. This challenge is further compounded for compressed models that were designed to deal with the high computational demands of deep neural networks. To address these challenges, we propose a novel approach that integrates a region proposal-based framework into the segmentation process. To evaluate the performance of the proposed framework, we conduct experiments on the PASCAL VOC dataset, which presents challenging backgrounds. We use two different segmentation models, UNet and SqueezeUNet, to evaluate the impact of region proposals on segmentation performance. Our experiments show that the incorporation of region proposals significantly improves segmentation accuracy and reduces false positive pixels in the background, leading to better overall performance. Specifically, the SqueezeUNet model achieves a mean Intersection over Union (mIoU) of 0.682, which is a 12% improvement over the baseline SqueezeUNet model without region proposals. Similarly, the UNet model achieves a mIoU of 0.678, which is a 13% improvement over the baseline UNet model without region proposals.
{"title":"Improving pedestrian segmentation using region proposal-based CNN semantic segmentation","authors":"M. J. Lahgazi, P. Argoul, A. Hakim","doi":"10.23939/mmc2023.03.854","DOIUrl":"https://doi.org/10.23939/mmc2023.03.854","url":null,"abstract":"Pedestrian segmentation is a critical task in computer vision, but it can be challenging for segmentation models to accurately classify pedestrians in images with challenging backgrounds and luminosity changes, as well as occlusions. This challenge is further compounded for compressed models that were designed to deal with the high computational demands of deep neural networks. To address these challenges, we propose a novel approach that integrates a region proposal-based framework into the segmentation process. To evaluate the performance of the proposed framework, we conduct experiments on the PASCAL VOC dataset, which presents challenging backgrounds. We use two different segmentation models, UNet and SqueezeUNet, to evaluate the impact of region proposals on segmentation performance. Our experiments show that the incorporation of region proposals significantly improves segmentation accuracy and reduces false positive pixels in the background, leading to better overall performance. Specifically, the SqueezeUNet model achieves a mean Intersection over Union (mIoU) of 0.682, which is a 12% improvement over the baseline SqueezeUNet model without region proposals. Similarly, the UNet model achieves a mIoU of 0.678, which is a 13% improvement over the baseline UNet model without region proposals.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68769502","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}
Machine learning algorithms play an important role in analyzing complex data in research across various fields. In this paper, we employ multiple regression algorithms and statistical techniques to investigate the relationship between objective and subjective quality of life indicators and reveal the key factors affecting happiness at the international level based on data from the Human Development Index and the World Happiness Index covering the period from 2015 to 2021. The Pearson correlation analysis showed that happiness is related to the HDI score and GNI per capita. The best-performing model for forecasting happiness was the random forest regression, with a R2 score of 0.93667, a mean squared error of 0.0033048, and a root mean squared error of 0.05748, followed by the XGBoost regression and the Decision Tree regression, respectively. These models indicated that GNI per capita is the most significant feature in predicting happiness.
{"title":"Machine learning for the analysis of quality of life using the World Happiness Index and Human Development Indicators","authors":"A. Jannani, N. Sael, F. Benabbou","doi":"10.23939/mmc2023.02.534","DOIUrl":"https://doi.org/10.23939/mmc2023.02.534","url":null,"abstract":"Machine learning algorithms play an important role in analyzing complex data in research across various fields. In this paper, we employ multiple regression algorithms and statistical techniques to investigate the relationship between objective and subjective quality of life indicators and reveal the key factors affecting happiness at the international level based on data from the Human Development Index and the World Happiness Index covering the period from 2015 to 2021. The Pearson correlation analysis showed that happiness is related to the HDI score and GNI per capita. The best-performing model for forecasting happiness was the random forest regression, with a R2 score of 0.93667, a mean squared error of 0.0033048, and a root mean squared error of 0.05748, followed by the XGBoost regression and the Decision Tree regression, respectively. These models indicated that GNI per capita is the most significant feature in predicting happiness.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68769072","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}
In comparison to fuzzy sets, intuitionistic fuzzy sets are much more efficient at representing and processing uncertainty. Distance measures quantify how much the information conveyed by intuitionistic fuzzy sets differs from one another. Researchers have suggested many distance measures to assess the difference between intuitionistic fuzzy sets, but several of them produce contradictory results in practice and violate the fundamental axioms of distance measure. In this article, we introduce a novel distance measure for IFSs, visualize it, and discuss its boundedness and nonlinear characteristics using appropriate numerical examples. In addition to establishing its validity, its effectiveness was investigated using real-life examples from multiple fields, such as medical diagnosis and pattern recognition. We also present a technique to solve pattern recognition problems, and the superiority of the proposed approach over existing approaches is demonstrated by incorporating a performance index in terms of "Degree of Confidence" (DOC). Finally, we extend the applicability of the proposed approach to establish a new decision-making approach known as the IFIR (Intuitionistic Fuzzy Inferior Ratio) method, and its efficiency is analyzed with other established decision-making approaches.
{"title":"Multi-criteria decision making based on novel distance measure in intuitionistic fuzzy environment","authors":"S. Kumar, R. Kumar","doi":"10.23939/mmc2023.02.359","DOIUrl":"https://doi.org/10.23939/mmc2023.02.359","url":null,"abstract":"In comparison to fuzzy sets, intuitionistic fuzzy sets are much more efficient at representing and processing uncertainty. Distance measures quantify how much the information conveyed by intuitionistic fuzzy sets differs from one another. Researchers have suggested many distance measures to assess the difference between intuitionistic fuzzy sets, but several of them produce contradictory results in practice and violate the fundamental axioms of distance measure. In this article, we introduce a novel distance measure for IFSs, visualize it, and discuss its boundedness and nonlinear characteristics using appropriate numerical examples. In addition to establishing its validity, its effectiveness was investigated using real-life examples from multiple fields, such as medical diagnosis and pattern recognition. We also present a technique to solve pattern recognition problems, and the superiority of the proposed approach over existing approaches is demonstrated by incorporating a performance index in terms of \"Degree of Confidence\" (DOC). Finally, we extend the applicability of the proposed approach to establish a new decision-making approach known as the IFIR (Intuitionistic Fuzzy Inferior Ratio) method, and its efficiency is analyzed with other established decision-making approaches.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68768486","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}
The article presents theoretical and applied aspects of modeling the financial flows' impact on the diagnosis of the economic security level of the enterprise with the main components of security. The functioning of enterprise's financial flow management models and the economic security level diagnostics applied models (the model of structural and functional diagnostics and the model of simulation modeling) are evaluated. The economic security loan repayment influence model and a set of criteria for assessing the effectiveness of financial flows are considered.
{"title":"Modeling the financial flows impact on the diagnosis of an enterprise's economic security level","authors":"I. Khoma, O. Gaiduchok, Kh. M. Markovych","doi":"10.23939/mmc2023.02.458","DOIUrl":"https://doi.org/10.23939/mmc2023.02.458","url":null,"abstract":"The article presents theoretical and applied aspects of modeling the financial flows' impact on the diagnosis of the economic security level of the enterprise with the main components of security. The functioning of enterprise's financial flow management models and the economic security level diagnostics applied models (the model of structural and functional diagnostics and the model of simulation modeling) are evaluated. The economic security loan repayment influence model and a set of criteria for assessing the effectiveness of financial flows are considered.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68768504","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}
K. Kamilu, M. I. Sulaiman, A. Muhammad, A. W. Mohamad, M. Mamat
In this paper, we construct a new conjugate gradient method for solving unconstrained optimization problems. The proposed method satisfies the sufficient decent property irrespective of the line search and the global convergence was established under some suitable. Further, the new method was used to train different sets of data via a feed forward neural network. Results obtained show that the proposed algorithm significantly reduces the computational time by speeding up the directional minimization with a faster convergence rate.
{"title":"Performance evaluation of a novel Conjugate Gradient Method for training feed forward neural network","authors":"K. Kamilu, M. I. Sulaiman, A. Muhammad, A. W. Mohamad, M. Mamat","doi":"10.23939/mmc2023.02.326","DOIUrl":"https://doi.org/10.23939/mmc2023.02.326","url":null,"abstract":"In this paper, we construct a new conjugate gradient method for solving unconstrained optimization problems. The proposed method satisfies the sufficient decent property irrespective of the line search and the global convergence was established under some suitable. Further, the new method was used to train different sets of data via a feed forward neural network. Results obtained show that the proposed algorithm significantly reduces the computational time by speeding up the directional minimization with a faster convergence rate.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68768702","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}
One of the important problems that urban residents suffer from is Traffic Congestion. It makes their life more stressful, it impacts several sides including the economy: by wasting time, fuel and productivity. Moreover, the psychological and physical health. That makes road authorities required to find solutions for reducing traffic congestion and guaranteeing security and safety on roads. To this end, detecting road users in real-time allows for providing features and information about specific road points. These last are useful for road managers and also for road users about congested points. The goal is to build a model to detect road users including vehicles and pedestrians using artificial intelligence especially machine learning and computer vision technologies. This paper provides an approach to detecting road users using as input a dataset of 22983 images, each image contains more than one of the target objects, generally about 81000 target objects, distributed on persons (pedestrians), cars, trucks/buses (vehicles), and also motorcycles/bicycles. The dataset used in this study is known as Common Objects in Context (MS COCO) published by Microsoft. Furthermore, six different models were built based on the approaches RCNN, Fast RCNN, Faster RCNN, Mask RCNN, and the 5th and the 7th versions of YOLO. In addition, a comparison of these models using evaluation metrics was provided. As a result, the chosen model is able to detect road users with more than 55% in terms of mean average precision.
交通拥堵是困扰城市居民的重要问题之一。它使他们的生活更有压力，它影响了包括经济在内的几个方面:浪费时间，燃料和生产力。此外，心理和身体的健康。这就要求道路管理部门找到减少交通拥堵和保障道路安全的解决方案。为此，实时检测道路使用者可以提供有关特定道路点的特征和信息。最后这些对于道路管理者和道路使用者来说都很有用。目标是建立一个模型，利用人工智能，特别是机器学习和计算机视觉技术，检测包括车辆和行人在内的道路使用者。本文提供了一种检测道路使用者的方法，使用22983张图像作为输入数据集，每张图像包含多个目标物体，通常约81000个目标物体，分布在人(行人)、汽车、卡车/公共汽车(车辆)以及摩托车/自行车上。本研究中使用的数据集是微软发布的Common Objects in Context (MS COCO)。此外，基于RCNN、Fast RCNN、Faster RCNN、Mask RCNN以及YOLO的第5版和第7版构建了6个不同的模型。此外，还使用评价指标对这些模型进行了比较。因此，所选择的模型能够以超过55%的平均精度检测道路使用者。
{"title":"Road users detection for traffic congestion classification","authors":"A. Es Swidi, S. Ardchir, A. Daif, M. Azouazi","doi":"10.23939/mmc2023.02.518","DOIUrl":"https://doi.org/10.23939/mmc2023.02.518","url":null,"abstract":"One of the important problems that urban residents suffer from is Traffic Congestion. It makes their life more stressful, it impacts several sides including the economy: by wasting time, fuel and productivity. Moreover, the psychological and physical health. That makes road authorities required to find solutions for reducing traffic congestion and guaranteeing security and safety on roads. To this end, detecting road users in real-time allows for providing features and information about specific road points. These last are useful for road managers and also for road users about congested points. The goal is to build a model to detect road users including vehicles and pedestrians using artificial intelligence especially machine learning and computer vision technologies. This paper provides an approach to detecting road users using as input a dataset of 22983 images, each image contains more than one of the target objects, generally about 81000 target objects, distributed on persons (pedestrians), cars, trucks/buses (vehicles), and also motorcycles/bicycles. The dataset used in this study is known as Common Objects in Context (MS COCO) published by Microsoft. Furthermore, six different models were built based on the approaches RCNN, Fast RCNN, Faster RCNN, Mask RCNN, and the 5th and the 7th versions of YOLO. In addition, a comparison of these models using evaluation metrics was provided. As a result, the chosen model is able to detect road users with more than 55% in terms of mean average precision.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68768992","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}
A system of non-Markovian transport equations is obtained for the non-equilibrium one-particle distribution function of particles and the non-equilibrium average value of the density of the potential energy of the interaction of the system particles far from the equilibrium state. Expressions for entropy, the partition function of the non-equilibrium state of the system, as well as non-equilibrium thermodynamic relations were obtained. The generalized structure of transfer nuclei is revealed in detail with the selection of short-range and long-range contributions of interactions between particles. The connection of transport nuclei with generalized diffusion coefficients, friction in the space of coordinates and momentum and the potential part of the thermal conductivity coefficient is established.
{"title":"Unification of kinetic and hydrodynamic approaches in the theory of dense gases and liquids far from equilibrium","authors":"M. V. Tokarchuk","doi":"10.23939/mmc2023.02.272","DOIUrl":"https://doi.org/10.23939/mmc2023.02.272","url":null,"abstract":"A system of non-Markovian transport equations is obtained for the non-equilibrium one-particle distribution function of particles and the non-equilibrium average value of the density of the potential energy of the interaction of the system particles far from the equilibrium state. Expressions for entropy, the partition function of the non-equilibrium state of the system, as well as non-equilibrium thermodynamic relations were obtained. The generalized structure of transfer nuclei is revealed in detail with the selection of short-range and long-range contributions of interactions between particles. The connection of transport nuclei with generalized diffusion coefficients, friction in the space of coordinates and momentum and the potential part of the thermal conductivity coefficient is established.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135585299","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}
In this paper, we have a discrete delayed dynamic system of three marine species: prey, predator, and superpredator. In addition to the effect of prey toxicity, we consider the negative fishing effect of these species. The study of this model consists of the search for equilibria with eigenvalue analysis, the existence of Hopf bifurcations at interior equilibria, and the determination of direction and stability analysis of Hopf bifurcation using the theory of normal form and center manifold. Some examples are given with numerical simulations to illustrate the results in different cases of delay.
{"title":"Study of Hopf bifurcation of delayed tritrophic system: dinoflagellates, mussels, and crabs","authors":"M. Hafdane, I. Agmour, Y. El Foutayeni","doi":"10.23939/mmc2023.01.066","DOIUrl":"https://doi.org/10.23939/mmc2023.01.066","url":null,"abstract":"In this paper, we have a discrete delayed dynamic system of three marine species: prey, predator, and superpredator. In addition to the effect of prey toxicity, we consider the negative fishing effect of these species. The study of this model consists of the search for equilibria with eigenvalue analysis, the existence of Hopf bifurcations at interior equilibria, and the determination of direction and stability analysis of Hopf bifurcation using the theory of normal form and center manifold. Some examples are given with numerical simulations to illustrate the results in different cases of delay.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134996611","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}
A. B. Vishalakshi, M. Kopp, U. Mahabaleshwar, I. Sarris
In the current analysis, ternary hybrid nanofluid flow with heat transfer under the influence of transpiration and radiation is explored. Partial differential equations (PDEs) of the current work are mapped by using a similarity variable to convert into ordinary differential equations (ODEs) form. The volume fractions of the ternary hybrid nanofluid are used in the entire calculation to achieve better results. The exact investigation of the momentum equation produces the domain value. The impact of thermal radiation is considered under energy equation and solved analytically with solution domain to yield the temperature profile. Graphical representations can be used to evaluate the effects of the factors thermal radiation, heat source or sink, and porous media. The present work is taken into consideration for numerous industrial applications.
{"title":"Ternary hybrid nanofluid flow caused by thermal radiation and mass transpiration in a porous stretching/shrinking sheet","authors":"A. B. Vishalakshi, M. Kopp, U. Mahabaleshwar, I. Sarris","doi":"10.23939/mmc2023.02.400","DOIUrl":"https://doi.org/10.23939/mmc2023.02.400","url":null,"abstract":"In the current analysis, ternary hybrid nanofluid flow with heat transfer under the influence of transpiration and radiation is explored. Partial differential equations (PDEs) of the current work are mapped by using a similarity variable to convert into ordinary differential equations (ODEs) form. The volume fractions of the ternary hybrid nanofluid are used in the entire calculation to achieve better results. The exact investigation of the momentum equation produces the domain value. The impact of thermal radiation is considered under energy equation and solved analytically with solution domain to yield the temperature profile. Graphical representations can be used to evaluate the effects of the factors thermal radiation, heat source or sink, and porous media. The present work is taken into consideration for numerous industrial applications.","PeriodicalId":37156,"journal":{"name":"Mathematical Modeling and Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68768554","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}
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