The Experts below are selected from a list of 216 Experts worldwide ranked by ideXlab platform

Damien Trentesaux - One of the best experts on this subject based on the ideXlab platform.

  • DoCEIS - Self-organized Holonic Manufacturing Systems Combining Adaptation and Performance Optimization
    Technological Innovation for Value Creation, 2012
    Co-Authors: José Barbosa, Paulo Leitão, Emmanuel Adam, Damien Trentesaux
    Abstract:

    Traditional manufacturing solutions, based on centralized structures, are ineffective in unpredictable and volatile scenarios. Recent manufacturing paradigms, such as Holonic Manufacturing Systems, handle better these unpredictable situations but aren’t able to achieve the performance optimization levels displayed by the classical centralized solutions when the system runs without perturbations. This paper introduces a holonic manufacturing architecture that considers biological insights, namely Emergence and Self-Organization, to achieve adaptation and responsiveness without degrading the performance optimization. For this purpose, Self-Organization and self-learning mechanisms embedded at micro and macro levels play an important role, as well the design of stabilizers to control the system nervousness in such dynamic and adaptive behaviour.

  • Self-organized Holonic Manufacturing Systems Combining Adaptation and Performance Optimization
    2012
    Co-Authors: José Barbosa, Paulo Leitão, Emmanuel Adam, Damien Trentesaux
    Abstract:

    Traditional manufacturing solutions, based on centralized structures, are ineffective in unpredictable and volatile scenarios. Recent manufacturing paradigms, such as Holonic Manufacturing Systems, handle better these unpredictable situations but aren’t able to achieve the performance optimization levels displayed by the classical centralized solutions when the system runs without perturbations. This paper introduces a holonic manufacturing architecture that considers biological insights, namely Emergence and Self-Organization, to achieve adaptation and responsiveness without degrading the performance optimization. For this purpose, Self-Organization and self-learning mechanisms embedded at micro and macro levels play an important role, as well the design of stabilizers to control the system nervousness in such dynamic and adaptive behaviour.

Manish P. Kurhekar - One of the best experts on this subject based on the ideXlab platform.

  • Agent based modeling of the process for initiation of Germinal Centers
    2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    The biological immune system is the progressive Complex Adaptive Systems (CASs) that consists of inhomogeneous and adaptive agents. It is an important defense mechanism in the human beings that generates an intricate cellular response against the foreign disturbances. It also exhibits prominent properties such as Emergence and Self-Organization. Bone marrow, thymus are primary and spleen, lymph nodes, tonsils, the adenoids, and MALT (Mucosa-associated lymphoid tissue) are secondary lymphoid organs that work with the immune system. After immunization or infection, due to intricate cellular dynamics Germinal Centers (GCs) are formed in the lymph nodes. There is an immediate need to understand intricate cellular dynamics during the process of initiation and formation of mature GC. There is an immediate need of immune system modeling to understand its intricate inbuilt mechanisms in the GC. Various mathematical and computational simulation approaches have been proposed for the modeling of the intricate dynamics of the complex biological immune system. There are two kinds of modeling techniques that are used to simulate the immune system: equation-based modeling and agent-based modeling. Due to some drawbacks of the equation-based simulation, agent-based modeling technique is used. In this paper, we proposed an agent-based model of the process of initiation GC. This model helps researchers to understand the structure of the immune cells Emergence during the GC formation and verify the hypotheses. This model can be easily employed as an educational tool in academics and a research tool in scientific disciplines for developing medicines that can keep a disease under control.

  • COMPLEX BIOLOGICAL IMMUNE SYSTEM THROUGH THE EYES OF DUAL-PHASE EVOLUTION
    Journal of Biological Systems, 2018
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as Emergence and Self-Organization that are caused due to the phas...

  • COMPLEX BIOLOGICAL IMMUNE SYSTEM THROUGH THE EYES OF DUAL-PHASE EVOLUTION
    Journal of Biological Systems, 2018
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as Emergence and Self-Organization that are caused due to the phase transitions. These transitions are observed because of the increase and decrease in the number of system components and their interactions. The immune system, which is one of the CASs, provides an adaptive response to the foreign molecules. Prior to this response, the immune system is present in the circulation state and during the response, it moves into the growth state, where the number of immune cells and their cell–cell contacts increase rapidly. The phase transitions from the circulation state to the growth state and then back to the circulation state cause the Emergence and Self-Organization of the immune system, respectively. There is a need to understand these complex cellular dynamics during the immune response. In this paper, we have proposed an integrated model of DPE, network theory, and the immune system that has helped to understand and analyze the phases and properties of the immune system. Analysis of the growth phase network is provided and it is concluded that this network exhibits scale-free nature following power law for the degree distribution of nodes.

  • A Dual-Phase Evolution Model of Emergency Myelopoiesis
    2018 International Conference on Bioinformatics and Systems Biology (BSB), 2018
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    The immune system is one of the progressive Complex Adaptive Systems (CASs) that generates cellular response against the foreign disturbances and also exhibits prominent properties such as Emergence and Self-Organization. In a steady state, where a localized infection is caused by the disturbances, the myeloid immune cells are continuously created in the bone marrow. Nevertheless, if the infection gets distributed throughout the body, then these immune cells are created in a larger quantity due to the myelopoiesis process to fulfill the increased demand. This demand leads to the state change in the system from its steady state to the demand adapted emergency myelopoiesis state causing cellular Emergence. After the infection, it returns to the steady state due to the Self-Organization. This immune response results in the phase transitions from steady state to emergency myelopoiesis state and back. Dual-phase evolution (DPE) is a process that brings Emergence and Self-Organization in the CASs due to the phase transitions. DPE allows the immune system to rest in one of the phases such as a steady phase (i.e., the local or poorly connected phase of the DPE) or an emergency phase (i.e., the global phase of the DPE due to the increased number of cells), although it is predominantly the steady phase. In this paper, we propose an integrated model of the emergency myelopoiesis, DPE, and network theory. This model helps to understand the cellular interactions during the phase transitions along with its prominent properties. It is concluded that during the global phase, the immune network exhibits scale-free property. This network further follows the power-law for the degree distribution of its nodes.

José Barbosa - One of the best experts on this subject based on the ideXlab platform.

  • DoCEIS - Self-organized Holonic Manufacturing Systems Combining Adaptation and Performance Optimization
    Technological Innovation for Value Creation, 2012
    Co-Authors: José Barbosa, Paulo Leitão, Emmanuel Adam, Damien Trentesaux
    Abstract:

    Traditional manufacturing solutions, based on centralized structures, are ineffective in unpredictable and volatile scenarios. Recent manufacturing paradigms, such as Holonic Manufacturing Systems, handle better these unpredictable situations but aren’t able to achieve the performance optimization levels displayed by the classical centralized solutions when the system runs without perturbations. This paper introduces a holonic manufacturing architecture that considers biological insights, namely Emergence and Self-Organization, to achieve adaptation and responsiveness without degrading the performance optimization. For this purpose, Self-Organization and self-learning mechanisms embedded at micro and macro levels play an important role, as well the design of stabilizers to control the system nervousness in such dynamic and adaptive behaviour.

  • Self-organized Holonic Manufacturing Systems Combining Adaptation and Performance Optimization
    2012
    Co-Authors: José Barbosa, Paulo Leitão, Emmanuel Adam, Damien Trentesaux
    Abstract:

    Traditional manufacturing solutions, based on centralized structures, are ineffective in unpredictable and volatile scenarios. Recent manufacturing paradigms, such as Holonic Manufacturing Systems, handle better these unpredictable situations but aren’t able to achieve the performance optimization levels displayed by the classical centralized solutions when the system runs without perturbations. This paper introduces a holonic manufacturing architecture that considers biological insights, namely Emergence and Self-Organization, to achieve adaptation and responsiveness without degrading the performance optimization. For this purpose, Self-Organization and self-learning mechanisms embedded at micro and macro levels play an important role, as well the design of stabilizers to control the system nervousness in such dynamic and adaptive behaviour.

Snehal B. Shinde - One of the best experts on this subject based on the ideXlab platform.

  • Agent based modeling of the process for initiation of Germinal Centers
    2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    The biological immune system is the progressive Complex Adaptive Systems (CASs) that consists of inhomogeneous and adaptive agents. It is an important defense mechanism in the human beings that generates an intricate cellular response against the foreign disturbances. It also exhibits prominent properties such as Emergence and Self-Organization. Bone marrow, thymus are primary and spleen, lymph nodes, tonsils, the adenoids, and MALT (Mucosa-associated lymphoid tissue) are secondary lymphoid organs that work with the immune system. After immunization or infection, due to intricate cellular dynamics Germinal Centers (GCs) are formed in the lymph nodes. There is an immediate need to understand intricate cellular dynamics during the process of initiation and formation of mature GC. There is an immediate need of immune system modeling to understand its intricate inbuilt mechanisms in the GC. Various mathematical and computational simulation approaches have been proposed for the modeling of the intricate dynamics of the complex biological immune system. There are two kinds of modeling techniques that are used to simulate the immune system: equation-based modeling and agent-based modeling. Due to some drawbacks of the equation-based simulation, agent-based modeling technique is used. In this paper, we proposed an agent-based model of the process of initiation GC. This model helps researchers to understand the structure of the immune cells Emergence during the GC formation and verify the hypotheses. This model can be easily employed as an educational tool in academics and a research tool in scientific disciplines for developing medicines that can keep a disease under control.

  • COMPLEX BIOLOGICAL IMMUNE SYSTEM THROUGH THE EYES OF DUAL-PHASE EVOLUTION
    Journal of Biological Systems, 2018
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as Emergence and Self-Organization that are caused due to the phas...

  • COMPLEX BIOLOGICAL IMMUNE SYSTEM THROUGH THE EYES OF DUAL-PHASE EVOLUTION
    Journal of Biological Systems, 2018
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as Emergence and Self-Organization that are caused due to the phase transitions. These transitions are observed because of the increase and decrease in the number of system components and their interactions. The immune system, which is one of the CASs, provides an adaptive response to the foreign molecules. Prior to this response, the immune system is present in the circulation state and during the response, it moves into the growth state, where the number of immune cells and their cell–cell contacts increase rapidly. The phase transitions from the circulation state to the growth state and then back to the circulation state cause the Emergence and Self-Organization of the immune system, respectively. There is a need to understand these complex cellular dynamics during the immune response. In this paper, we have proposed an integrated model of DPE, network theory, and the immune system that has helped to understand and analyze the phases and properties of the immune system. Analysis of the growth phase network is provided and it is concluded that this network exhibits scale-free nature following power law for the degree distribution of nodes.

  • A Dual-Phase Evolution Model of Emergency Myelopoiesis
    2018 International Conference on Bioinformatics and Systems Biology (BSB), 2018
    Co-Authors: Snehal B. Shinde, Manish P. Kurhekar
    Abstract:

    The immune system is one of the progressive Complex Adaptive Systems (CASs) that generates cellular response against the foreign disturbances and also exhibits prominent properties such as Emergence and Self-Organization. In a steady state, where a localized infection is caused by the disturbances, the myeloid immune cells are continuously created in the bone marrow. Nevertheless, if the infection gets distributed throughout the body, then these immune cells are created in a larger quantity due to the myelopoiesis process to fulfill the increased demand. This demand leads to the state change in the system from its steady state to the demand adapted emergency myelopoiesis state causing cellular Emergence. After the infection, it returns to the steady state due to the Self-Organization. This immune response results in the phase transitions from steady state to emergency myelopoiesis state and back. Dual-phase evolution (DPE) is a process that brings Emergence and Self-Organization in the CASs due to the phase transitions. DPE allows the immune system to rest in one of the phases such as a steady phase (i.e., the local or poorly connected phase of the DPE) or an emergency phase (i.e., the global phase of the DPE due to the increased number of cells), although it is predominantly the steady phase. In this paper, we propose an integrated model of the emergency myelopoiesis, DPE, and network theory. This model helps to understand the cellular interactions during the phase transitions along with its prominent properties. It is concluded that during the global phase, the immune network exhibits scale-free property. This network further follows the power-law for the degree distribution of its nodes.

José Barata - One of the best experts on this subject based on the ideXlab platform.

  • Self-organizing multiagent mechatronic systems in perspective
    2013 11th IEEE International Conference on Industrial Informatics (INDIN), 2013
    Co-Authors: Luis Ribeiro, José Barata
    Abstract:

    This paper discusses the main problematic, misunderstandings and gaps associated with the development of self-organizing multiagent mechatronic systems. The paper reflects the authors' experience in designing and implementing Multiagent Mechatronic Systems. It also partly addresses the work developed under the FP7 IDEAS project (rated an EU FP7 success story) as a clarifying, but not unique, example. In this respect the paper presents a critical overview on how the existing technology is close to support the automation concepts envisioned by emerging production paradigms that rely on Emergence and Self-Organization as main constructs of the system and why technology alone should be understand as only a mean and not a end.

  • INDIN - Self-organizing multiagent mechatronic systems in perspective
    2013 11th IEEE International Conference on Industrial Informatics (INDIN), 2013
    Co-Authors: Luis Ribeiro, José Barata
    Abstract:

    This paper discusses the main problematic, misunderstandings and gaps associated with the development of self-organizing multiagent mechatronic systems. The paper reflects the authors' experience in designing and implementing Multiagent Mechatronic Systems. It also partly addresses the work developed under the FP7 IDEAS project (rated an EU FP7 success story) as a clarifying, but not unique, example. In this respect the paper presents a critical overview on how the existing technology is close to support the automation concepts envisioned by emerging production paradigms that rely on Emergence and Self-Organization as main constructs of the system and why technology alone should be understand as only a mean and not a end.