This paper presents a novel metaheuristic binary crow search algorithm (CSA) designed for positive-unlabeled (PU) learning, a paradigm where only positive and unlabeled data are available, with applications in many diversified fields, such as medical diagnosis and fraud detection. The algorithm represent a useful adaptation of CSA, itself inspired by the food-hiding behavior of crows. The proposed BiCSA-PUL (binary crow search algorithm for positive-unlabeled learning) selects reliable negative samples from unlabeled data using binary vectors, and updates positions employing Hamming distance, guided by a modified F1-score, as fitness function. The algorithm was tested on 30 samples from 10 diverse datasets, outperforming seven state-of-the-art PU learning methods. The results reveal that BiCSA-PUL provides a robust and efficient approach for PU learning, significantly improving fitness and reliability. This work opens new avenues for applying metaheuristic optimization methods to challenging classification problems with limited labeled data. The main limitations are the potentially time-intensive process of parameters tuning and reliance on initial sampling.

This paper presents a novel metaheuristic binary crow search algorithm (CSA) designed for positive-unlabeled (PU) learning, a paradigm where only positive and unlabeled data are available, with applications in many diversified fields, such as medical diagnosis and fraud detection. The algorithm represent a useful adaptation of CSA, itself inspired by the food-hiding behavior of crows. The proposed BiCSA-PUL (binary crow search algorithm for positive-unlabeled learning) selects reliable negative samples from unlabeled data using binary vectors, and updates positions employing Hamming distance, guided by a modified F1-score, as fitness function. The algorithm was tested on 30 samples from 10 diverse datasets, outperforming seven state-of-the-art PU learning methods. The results reveal that BiCSA-PUL provides a robust and efficient approach for PU learning, significantly improving fitness and reliability. This work opens new avenues for applying metaheuristic optimization methods to challenging classification problems with limited labeled data. The main limitations are the potentially time-intensive process of parameters tuning and reliance on initial sampling.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

The global wind energy industry achieved a significant milestone by reaching a total capacity of one terawatt (TW) by the end of 2023, underscoring the increasing importance of wind energy as a sustainable energy source (Global Wind Energy Outlook, 2022). This study focuses on the simulation and dynamic analysis of an H-Darrieus wind turbine rotor using 3D Finite Element Analysis (FEA). Key structural parameters, including natural frequencies, associated vibration modes, and mass participation rates, were determined to optimize the rotor performance. A novel blade design is proposed in this work, offering a lighter and more robust alternative to traditional rotor blades manufactured from composites, like fiberglass-polyester, fiberglass-epoxy, or combinations with wood and carbon. The lighter design enhances the startup performance at low wind speeds, while the improved strength and fixing mechanisms ensure resilience against the increasingly severe sandstorms reported in recent years. The vibration dynamics of the rotor under critical wind loads were analyzed using the SolidWorks Simulation software, yielding highly satisfactory results. The stability and reliability of the rotor were validated, as the dynamic performance indices, and the quality criteria meet the requirements for optimal operation.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.

Let (X,d,μ) be a space of homogeneous type and L be a nonnegative self-adjoint operator on L2(X) whose heat kernels satisfy Gaussian upper bounds. In this article, we introduce the weighted variable Besov space associated with the operator L and demonstrate that Peetre maximal functions can be used to characterize this space. Furthermore, we provide a detailed study of its atomic decompositions.

An experimental investigation was conducted at Delft University of Technology to examine the behavior of eight statically loaded extended end plate moment connections up to collapse. The parameters investigated were the end plate thickness (10 mm, 15 mm, and 20 mm) and steel grade of the end plate (S355, S690). While the study was limited to a static test, this investigation intends to analyze the dynamic behavior of the research specimens (FS1 to FS4) using finite element methods. The multi-purpose software Abaqus was used to develop the 3D model. The mechanical properties of these connections, including strength, ductility, and energy dissipation capacity, are examined. The cyclic loading is applied according to the JGJ 101-96 standard specification. The finite element model was validated against experimental tests for both static and dynamic conditions, successfully reproducing moment-rotation curves and simulating ductile damage as well. The results indicate that increased plate thickness corresponds to improved stiffness and strength, while the use of higher steel grades introduces a delayed yield point and may reduce ductility, which must be balanced to optimize performance considering specific design requirements and loading conditions. Our findings align with previous findings and underscore the need for a better understanding of joint behavior under dynamic loading for seismic design since the strain rate at which load is applied significantly affects the material properties, which can significantly affect the performance of blast-resistant structures.

An experimental investigation was conducted at Delft University of Technology to examine the behavior of eight statically loaded extended end plate moment connections up to collapse. The parameters investigated were the end plate thickness (10 mm, 15 mm, and 20 mm) and steel grade of the end plate (S355, S690). While the study was limited to a static test, this investigation intends to analyze the dynamic behavior of the research specimens (FS1 to FS4) using finite element methods. The multi-purpose software Abaqus was used to develop the 3D model. The mechanical properties of these connections, including strength, ductility, and energy dissipation capacity, are examined. The cyclic loading is applied according to the JGJ 101-96 standard specification. The finite element model was validated against experimental tests for both static and dynamic conditions, successfully reproducing moment-rotation curves and simulating ductile damage as well. The results indicate that increased plate thickness corresponds to improved stiffness and strength, while the use of higher steel grades introduces a delayed yield point and may reduce ductility, which must be balanced to optimize performance considering specific design requirements and loading conditions. Our findings align with previous findings and underscore the need for a better understanding of joint behavior under dynamic loading for seismic design since the strain rate at which load is applied significantly affects the material properties, which can significantly affect the performance of blast-resistant structures.

An experimental investigation was conducted at Delft University of Technology to examine the behavior of eight statically loaded extended end plate moment connections up to collapse. The parameters investigated were the end plate thickness (10 mm, 15 mm, and 20 mm) and steel grade of the end plate (S355, S690). While the study was limited to a static test, this investigation intends to analyze the dynamic behavior of the research specimens (FS1 to FS4) using finite element methods. The multi-purpose software Abaqus was used to develop the 3D model. The mechanical properties of these connections, including strength, ductility, and energy dissipation capacity, are examined. The cyclic loading is applied according to the JGJ 101-96 standard specification. The finite element model was validated against experimental tests for both static and dynamic conditions, successfully reproducing moment-rotation curves and simulating ductile damage as well. The results indicate that increased plate thickness corresponds to improved stiffness and strength, while the use of higher steel grades introduces a delayed yield point and may reduce ductility, which must be balanced to optimize performance considering specific design requirements and loading conditions. Our findings align with previous findings and underscore the need for a better understanding of joint behavior under dynamic loading for seismic design since the strain rate at which load is applied significantly affects the material properties, which can significantly affect the performance of blast-resistant structures.

An experimental investigation was conducted at Delft University of Technology to examine the behavior of eight statically loaded extended end plate moment connections up to collapse. The parameters investigated were the end plate thickness (10 mm, 15 mm, and 20 mm) and steel grade of the end plate (S355, S690). While the study was limited to a static test, this investigation intends to analyze the dynamic behavior of the research specimens (FS1 to FS4) using finite element methods. The multi-purpose software Abaqus was used to develop the 3D model. The mechanical properties of these connections, including strength, ductility, and energy dissipation capacity, are examined. The cyclic loading is applied according to the JGJ 101-96 standard specification. The finite element model was validated against experimental tests for both static and dynamic conditions, successfully reproducing moment-rotation curves and simulating ductile damage as well. The results indicate that increased plate thickness corresponds to improved stiffness and strength, while the use of higher steel grades introduces a delayed yield point and may reduce ductility, which must be balanced to optimize performance considering specific design requirements and loading conditions. Our findings align with previous findings and underscore the need for a better understanding of joint behavior under dynamic loading for seismic design since the strain rate at which load is applied significantly affects the material properties, which can significantly affect the performance of blast-resistant structures.

An experimental investigation was conducted at Delft University of Technology to examine the behavior of eight statically loaded extended end plate moment connections up to collapse. The parameters investigated were the end plate thickness (10 mm, 15 mm, and 20 mm) and steel grade of the end plate (S355, S690). While the study was limited to a static test, this investigation intends to analyze the dynamic behavior of the research specimens (FS1 to FS4) using finite element methods. The multi-purpose software Abaqus was used to develop the 3D model. The mechanical properties of these connections, including strength, ductility, and energy dissipation capacity, are examined. The cyclic loading is applied according to the JGJ 101-96 standard specification. The finite element model was validated against experimental tests for both static and dynamic conditions, successfully reproducing moment-rotation curves and simulating ductile damage as well. The results indicate that increased plate thickness corresponds to improved stiffness and strength, while the use of higher steel grades introduces a delayed yield point and may reduce ductility, which must be balanced to optimize performance considering specific design requirements and loading conditions. Our findings align with previous findings and underscore the need for a better understanding of joint behavior under dynamic loading for seismic design since the strain rate at which load is applied significantly affects the material properties, which can significantly affect the performance of blast-resistant structures.

An experimental investigation was conducted at Delft University of Technology to examine the behavior of eight statically loaded extended end plate moment connections up to collapse. The parameters investigated were the end plate thickness (10 mm, 15 mm, and 20 mm) and steel grade of the end plate (S355, S690). While the study was limited to a static test, this investigation intends to analyze the dynamic behavior of the research specimens (FS1 to FS4) using finite element methods. The multi-purpose software Abaqus was used to develop the 3D model. The mechanical properties of these connections, including strength, ductility, and energy dissipation capacity, are examined. The cyclic loading is applied according to the JGJ 101-96 standard specification. The finite element model was validated against experimental tests for both static and dynamic conditions, successfully reproducing moment-rotation curves and simulating ductile damage as well. The results indicate that increased plate thickness corresponds to improved stiffness and strength, while the use of higher steel grades introduces a delayed yield point and may reduce ductility, which must be balanced to optimize performance considering specific design requirements and loading conditions. Our findings align with previous findings and underscore the need for a better understanding of joint behavior under dynamic loading for seismic design since the strain rate at which load is applied significantly affects the material properties, which can significantly affect the performance of blast-resistant structures.

Maintenance, storage and warehousing are complex processes required in many industries such as automotive, aerospace, manufacturing and logistic companies. These processes, often, involve moving objects in crowded environments using robots or human operators. Particularly, replacement and assembly of machine parts in crowded environments when performed by a human being require high technical skills. These tasks may be performed using robots to reduce costs due to human errors and execution time. However, robots under open world assumptions could neither operate in all environments nor perform tasks not modeled by the designer. In this paper, we introduce a mixed reality system to assist human operators in moving objects in crowded environments for maintenance tasks such as: parts assembly or replacement, and storage of objects. The introduced system consists of a mobile application exploited through a hands-free VR box. The proposed Mixed Reality for Industrial Maintenance (MRIM) system enhances the perception of a human operator by overlaying 3D real world visual information and virtual objects, such as: orientation guidelines including rotating angles, moving direction and displacement of carried objects. These guidelines allow for gaining execution time, and reducing human errors that might cause industrial parts damage. The proposed work brings two main contributions. First, it makes use of a new algorithm based on recasting, named R star (R*) that allows for optimizing pathfinding in 3D space. This later outperforms the two commonly used baseline 3D pathfinding algorithms of at least 87.5% in terms of execution time. Second, MRIM provides an easy-to-use interface that exploits information provided by the R* algorithm. The experiments, conducted in real condition for the task of part replacement in a crowded environment, show that MRIM reduces considerably execution time and human errors.

Maintenance, storage and warehousing are complex processes required in many industries such as automotive, aerospace, manufacturing and logistic companies. These processes, often, involve moving objects in crowded environments using robots or human operators. Particularly, replacement and assembly of machine parts in crowded environments when performed by a human being require high technical skills. These tasks may be performed using robots to reduce costs due to human errors and execution time. However, robots under open world assumptions could neither operate in all environments nor perform tasks not modeled by the designer. In this paper, we introduce a mixed reality system to assist human operators in moving objects in crowded environments for maintenance tasks such as: parts assembly or replacement, and storage of objects. The introduced system consists of a mobile application exploited through a hands-free VR box. The proposed Mixed Reality for Industrial Maintenance (MRIM) system enhances the perception of a human operator by overlaying 3D real world visual information and virtual objects, such as: orientation guidelines including rotating angles, moving direction and displacement of carried objects. These guidelines allow for gaining execution time, and reducing human errors that might cause industrial parts damage. The proposed work brings two main contributions. First, it makes use of a new algorithm based on recasting, named R star (R*) that allows for optimizing pathfinding in 3D space. This later outperforms the two commonly used baseline 3D pathfinding algorithms of at least 87.5% in terms of execution time. Second, MRIM provides an easy-to-use interface that exploits information provided by the R* algorithm. The experiments, conducted in real condition for the task of part replacement in a crowded environment, show that MRIM reduces considerably execution time and human errors.

Maintenance, storage and warehousing are complex processes required in many industries such as automotive, aerospace, manufacturing and logistic companies. These processes, often, involve moving objects in crowded environments using robots or human operators. Particularly, replacement and assembly of machine parts in crowded environments when performed by a human being require high technical skills. These tasks may be performed using robots to reduce costs due to human errors and execution time. However, robots under open world assumptions could neither operate in all environments nor perform tasks not modeled by the designer. In this paper, we introduce a mixed reality system to assist human operators in moving objects in crowded environments for maintenance tasks such as: parts assembly or replacement, and storage of objects. The introduced system consists of a mobile application exploited through a hands-free VR box. The proposed Mixed Reality for Industrial Maintenance (MRIM) system enhances the perception of a human operator by overlaying 3D real world visual information and virtual objects, such as: orientation guidelines including rotating angles, moving direction and displacement of carried objects. These guidelines allow for gaining execution time, and reducing human errors that might cause industrial parts damage. The proposed work brings two main contributions. First, it makes use of a new algorithm based on recasting, named R star (R*) that allows for optimizing pathfinding in 3D space. This later outperforms the two commonly used baseline 3D pathfinding algorithms of at least 87.5% in terms of execution time. Second, MRIM provides an easy-to-use interface that exploits information provided by the R* algorithm. The experiments, conducted in real condition for the task of part replacement in a crowded environment, show that MRIM reduces considerably execution time and human errors.

Maintenance, storage and warehousing are complex processes required in many industries such as automotive, aerospace, manufacturing and logistic companies. These processes, often, involve moving objects in crowded environments using robots or human operators. Particularly, replacement and assembly of machine parts in crowded environments when performed by a human being require high technical skills. These tasks may be performed using robots to reduce costs due to human errors and execution time. However, robots under open world assumptions could neither operate in all environments nor perform tasks not modeled by the designer. In this paper, we introduce a mixed reality system to assist human operators in moving objects in crowded environments for maintenance tasks such as: parts assembly or replacement, and storage of objects. The introduced system consists of a mobile application exploited through a hands-free VR box. The proposed Mixed Reality for Industrial Maintenance (MRIM) system enhances the perception of a human operator by overlaying 3D real world visual information and virtual objects, such as: orientation guidelines including rotating angles, moving direction and displacement of carried objects. These guidelines allow for gaining execution time, and reducing human errors that might cause industrial parts damage. The proposed work brings two main contributions. First, it makes use of a new algorithm based on recasting, named R star (R*) that allows for optimizing pathfinding in 3D space. This later outperforms the two commonly used baseline 3D pathfinding algorithms of at least 87.5% in terms of execution time. Second, MRIM provides an easy-to-use interface that exploits information provided by the R* algorithm. The experiments, conducted in real condition for the task of part replacement in a crowded environment, show that MRIM reduces considerably execution time and human errors.

Soil erosion is the main cause of siltation in dams, on the one hand, and it is one of the main causes of degradation of the agro-pedological heritage, on the other hand. In this context, this work aims to quantify the eroded soils and their spatial distribution in the watershed of Wadi El-Hai (Aurès, Algeria), reaching the Fontaines des Gazelles dam located at the outlet of this basin. The work focuses on mapping and analyzing various thematic maps representing the key erosion factors, linking the Revised Universal Soil Loss Equation (RUSLE), with the goal of producing a synthesis map providing a quantitative spatial representation of the extent of the phenomenon in the watershed. From this map, we can confirm that the erosion phenomenon affects the entire watershed of Wad El Hai. The most severe erosion, affecting 11.60 % of the expansive territory at rates exceeding 33.6 tons per year per hectare, is predominantly concentrated in mountainous regions marked by exceptionally steep slopes. Conversely, the majority, accounting for 64.23% of the entire expanse, is situated in the plains, where erosion rates are comparatively lower at 6.7 tons per hectare per year. The assessment of potential water erosion yields disconcerting outcomes, projecting an average annual loss rate of 15.38 tons per hectare throughout the entire catchment area. The results presented in this study will serve as a vital resource and a decision-making tool, supporting the management and preservation of natural resources by policymakers and stakeholders.

Soil erosion is the main cause of siltation in dams, on the one hand, and it is one of the main causes of degradation of the agro-pedological heritage, on the other hand. In this context, this work aims to quantify the eroded soils and their spatial distribution in the watershed of Wadi El-Hai (Aurès, Algeria), reaching the Fontaines des Gazelles dam located at the outlet of this basin. The work focuses on mapping and analyzing various thematic maps representing the key erosion factors, linking the Revised Universal Soil Loss Equation (RUSLE), with the goal of producing a synthesis map providing a quantitative spatial representation of the extent of the phenomenon in the watershed. From this map, we can confirm that the erosion phenomenon affects the entire watershed of Wad El Hai. The most severe erosion, affecting 11.60 % of the expansive territory at rates exceeding 33.6 tons per year per hectare, is predominantly concentrated in mountainous regions marked by exceptionally steep slopes. Conversely, the majority, accounting for 64.23% of the entire expanse, is situated in the plains, where erosion rates are comparatively lower at 6.7 tons per hectare per year. The assessment of potential water erosion yields disconcerting outcomes, projecting an average annual loss rate of 15.38 tons per hectare throughout the entire catchment area. The results presented in this study will serve as a vital resource and a decision-making tool, supporting the management and preservation of natural resources by policymakers and stakeholders.