Wico Mulder - Academia.edu (original) (raw)

Papers by Wico Mulder

Geophysics 77 2012, Aug 9, 2012

Frequency-to-time transformations are of interest to controlled-source electromagnetic methods wh... more Frequency-to-time transformations are of interest to controlled-source electromagnetic methods when time-domain data are inverted for a subsurface resistivity model by numerical frequency-domain modeling at a selected, small number of frequencies whereas the data misfit is determined in the time domain. We propose an efficient, Prony-type method using frequency-domain diffusive-field basis functions for which the time-domain equivalents are known. Diffusive fields are characterized by an exponential part whose argument is proportional to the square root of frequency and a part that is polynomial in integer powers of the square root of frequency. Data at a limited number of frequencies suffice for the transformation back to the time. In the exponential part, several diffusion-time values must be chosen. Once a suitable range of diffusion-time values are found, the method is quite robust in the number of values used. The highest power in the polynomial part can be determined from the source and receiver type. When the frequency-domain data are accurately approximated by the basis functions, the timedomain result is also accurate. This method is accurate over a wider time range than other methods and has the correct late-time asymptotic behavior. The method works well for data computed for layered and 3D subsurface models.

International Journal of Public Health, 2016

Since the extent of sick leave and the problems of vocational school students are relatively larg... more Since the extent of sick leave and the problems of vocational school students are relatively large, we aimed to tailor a sick leave protocol at Dutch lower secondary education schools to the particular context of vocational schools. Four steps of the iterative process of Intervention Mapping (IM) to adapt this protocol were carried out: (1) performing a needs assessment and defining a program objective, (2) determining the performance and change objectives, (3) identifying theory-based methods and practical strategies and (4) developing a program plan. Interviews with students using structured questionnaires, in-depth interviews with relevant stakeholders, a literature research and, finally, a pilot implementation were carried out. A sick leave protocol was developed that was feasible and acceptable for all stakeholders. The main barriers for widespread implementation are time constraints in both monitoring and acting upon sick leave by school and youth health care. The iterative process of IM has shown its merits in the adaptation of the manual 'A quick return to school is much better' to a sick leave protocol for vocational school students.

Ifip Tc5 Wg5 5 Publications, 2004

Caries Res, May 1, 2009

This paper proposes a distributed learning mechanism that learns patterns from distributed datase... more This paper proposes a distributed learning mechanism that learns patterns from distributed datasets. The complex and dynamic settings of grid environments requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. We developed an information system, based on collaborative agents, that supports system administrators in monitoring the grid. While observing log files, the agents learn traffic patterns in their own local domain of the grid. The agents represent their knowledge in the form of deterministic finite automata (DFA), and share their models to provide global or multi-domain overviews. We discuss our collaborative learning mechanism and show the results of our experiments with data of two grid-sites. Our system generated jobtraffic overviews that gave new insights in the performance of the grid environment.

In distributed service oriented ICT environments, where broker components control and delegate th... more In distributed service oriented ICT environments, where broker components control and delegate the work to appropriate services, the value of information that these brokers use in their mechanisms is found to be prone to the dynamics of the infrastructure. In this paper we describe our research on anticipating brokers that make use of predictive information services. We start with a

In-vehicle information management is vital in intelligent traffic systems. In this paper we motiv... more In-vehicle information management is vital in intelligent traffic systems. In this paper we motivate an architecture for ontology-based context-aware reasoning for in-vehicle information management. Ontology- based reasoning allows context-awareness, inference and advanced reasoning capabilities. However, the amount of computational power it requires often conflicts with the computational limitations of on-board units, as well as the high demand for timeliness and safety. Our approach uses ontology-based reasoning and a finite state machine (FSM). By combining ontology and FSM, we illustrate how a heavy-weight reasoning-solution could be applied in a light-weight computational environment.

ABSTRACT This paper proposes a distributed learning mechanism that learns patterns from distribut... more ABSTRACT This paper proposes a distributed learning mechanism that learns patterns from distributed datasets. The complex and dynamic settings of grid environments requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. We developed an information system, based on collaborative agents, that supports system administrators in monitoring the grid. While observing log files, the agents learn traffic patterns in their own local domain of the grid. The agents represent their knowledge in the form of deterministic finite automata (DFA), and share their models to provide global or multi-domain overviews. We discuss our collaborative learning mechanism and show the results of our experiments with data of two grid-sites. Our system generated job-traffic overviews that gave new insights in the performance of the grid environment.

Lecture Notes in Computer Science, 2008

Service oriented systems need to be maintained to keep the requested level of service. This is ch... more Service oriented systems need to be maintained to keep the requested level of service. This is challenge in large grid-and saas based networks that are managed by numerous entities. This paper is about supporting multi agent systems that operate in the network and support its management by learning actual structures from life observed logging data. We focus on a collaborative grammar induction mechanism in which agents share local models in order to retrieve a model of the structure of the total service network. We studied the performance of groups of agents while varying the size and degree of communication. We motivate the application of the mechanism in the domain of service oriented system and show the results of experiments using a distributed agent-based monitoring system. We promote further research in the overlapping scientific disciplines of multi agent systems and machine learning in the application domain of service oriented systems.

Lecture Notes in Computer Science, 2013

ABSTRACT Grid monitoring requires analysis of large amounts of log files across multiple domains.... more ABSTRACT Grid monitoring requires analysis of large amounts of log files across multiple domains. An approach is described for automated extraction of job-flow information from large computer grids, using software agents and genetic computation. A prototype was created as a first step towards communities of agents that will collaborate to learn log-file structures and exchange knowledge across organizational domains.

Lecture Notes in Computer Science, 2010

ABSTRACT We introduce a formal paradigm to study global adaptive behavior of organizations of col... more ABSTRACT We introduce a formal paradigm to study global adaptive behavior of organizations of collaborative agents with local learning capabilities. Our model is based on an extension of the classical language learning setting in which a teacher provides examples to a student that must guess a correct grammar. In our model the teacher is transformed in to a workload dispatcher and the student is replaced by an organization of worker-agents. The jobs that the dispatcher creates consist of sequences of tasks that can be modeled as sentences of a language. The agents in the organization have language learning capabilities that can be used to learn local work-distribution strategies. In this context one can study the conditions under which the organization can adapt itself to structural pressure from an environment. We show that local learning capabilities contribute to global performance improvements. We have implemented our theoretical framework in a workbench that can be used to run simulations. We discuss some results of these simulations. We believe that this approach provides a viable framework to study processes of self-organization and optimization of collaborative agent networks.

Methods and Tools for Collaborative Networked Organizations, 2008

IFIP International Federation for Information Processing, 2004

This paper addresses the area of software development and maintenance for GRID- based application... more This paper addresses the area of software development and maintenance for GRID- based applications. We argue that the structure and geographical spread of these systems poses new challenges to the ICT services industry. We believe that human intelligence and related skills are a central element in facing these challenges and see the emerging paradigm of virtual organizations as promising direction

Lecture Notes in Computer Science, 2010

ABSTRACT We show that within the Gold paradigm for language learning an informer for a superfinit... more ABSTRACT We show that within the Gold paradigm for language learning an informer for a superfinite set can cause an optimal MDL learner to make an infinite amount of mind changes. In this setting an optimal learner can make an infinite amount of wrong choices without approximating the right solution. This result helps us to understand the relation between MDL and identification in the limit in learning: MDL is an optimal model selection paradigm, identification in the limit defines recursion theoretical conditions for convergence of a learner.

Methods and Tools for Collaborative Networked Organizations, 2008

Lecture Notes in Computer Science, 2007

In e-Science, scientific workflow systems are used to share data and knowledge in collaborative e... more In e-Science, scientific workflow systems are used to share data and knowledge in collaborative experiments. In recent work we discussed the concepts of a workflow bus [1], allowing multiple workflow systems to be coupled in a meta-workflow system with multiple execution models. In this paper we propose an approach for a formal model to perform the task of reasoning of about the execution models of such workflow systems. We show that I/O Automata can be used as a formalism to prove the correctness of complicated workflows involving multiple workflow engines and execution models.

Proceedings of the 6th international conference industry session on Grids meets autonomic computing - GMAC '09, 2009

The complex and dynamic settings of grid environments lead to challenges on their operational mai... more The complex and dynamic settings of grid environments lead to challenges on their operational maintenance. The growth of these environments in terms of size and usage requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. Communication across organizational domains and interoperability between existing monitoring tools is subject to improvement. In this paper we present an information system, based on collaborative agents, that supports system administrators in monitoring the grid. While observing log files, the agents learn patterns about job-traffic in their own local domain of the grid and share information to provide global or multi-domain overviews. The agents represent their knowledge in the form of deterministic finite automata (DFA). We discuss our collaborative learning mechanism and show the results of our experiments with data of two grid-sites. Our system generated job-traffic overviews that gave new insights in the performance of the grid environment.

GEOPHYSICS, 2008

We modeled time-domain EM measurements of induction currents for marine and land applications wit... more We modeled time-domain EM measurements of induction currents for marine and land applications with a frequencydomain code.An analysis of the computational complexity of a number of numerical methods shows that frequency-domain modeling followed by a Fourier transform is an attractive choice if a sufficiently powerful solver is available. A recently developed, robust multigrid solver meets this requirement. An interpolation criterion determined the automatic selection of frequencies. The skin depth controlled the construction of the computational grid at each frequency. Tests of the method against exact solutions for some simple problems and a realistic marine example demonstrate that a limited number of frequencies suffice to provide time-domain solutions after piecewise-cubic Hermite interpolation and a fast Fourier transform.

Network-Centric Collaboration and Supporting …, 2006

Information retrieval is one of the key processes in the management of collaborative networks (CN... more Information retrieval is one of the key processes in the management of collaborative networks (CNs). For large and complex networks manual processes need to be supported by automated retrieval systems. We study the characteristics of information retrieval ...

Geophysics 77 2012, Aug 9, 2012

Frequency-to-time transformations are of interest to controlled-source electromagnetic methods wh... more Frequency-to-time transformations are of interest to controlled-source electromagnetic methods when time-domain data are inverted for a subsurface resistivity model by numerical frequency-domain modeling at a selected, small number of frequencies whereas the data misfit is determined in the time domain. We propose an efficient, Prony-type method using frequency-domain diffusive-field basis functions for which the time-domain equivalents are known. Diffusive fields are characterized by an exponential part whose argument is proportional to the square root of frequency and a part that is polynomial in integer powers of the square root of frequency. Data at a limited number of frequencies suffice for the transformation back to the time. In the exponential part, several diffusion-time values must be chosen. Once a suitable range of diffusion-time values are found, the method is quite robust in the number of values used. The highest power in the polynomial part can be determined from the source and receiver type. When the frequency-domain data are accurately approximated by the basis functions, the timedomain result is also accurate. This method is accurate over a wider time range than other methods and has the correct late-time asymptotic behavior. The method works well for data computed for layered and 3D subsurface models.

International Journal of Public Health, 2016

Since the extent of sick leave and the problems of vocational school students are relatively larg... more Since the extent of sick leave and the problems of vocational school students are relatively large, we aimed to tailor a sick leave protocol at Dutch lower secondary education schools to the particular context of vocational schools. Four steps of the iterative process of Intervention Mapping (IM) to adapt this protocol were carried out: (1) performing a needs assessment and defining a program objective, (2) determining the performance and change objectives, (3) identifying theory-based methods and practical strategies and (4) developing a program plan. Interviews with students using structured questionnaires, in-depth interviews with relevant stakeholders, a literature research and, finally, a pilot implementation were carried out. A sick leave protocol was developed that was feasible and acceptable for all stakeholders. The main barriers for widespread implementation are time constraints in both monitoring and acting upon sick leave by school and youth health care. The iterative process of IM has shown its merits in the adaptation of the manual 'A quick return to school is much better' to a sick leave protocol for vocational school students.

Ifip Tc5 Wg5 5 Publications, 2004

Caries Res, May 1, 2009

This paper proposes a distributed learning mechanism that learns patterns from distributed datase... more This paper proposes a distributed learning mechanism that learns patterns from distributed datasets. The complex and dynamic settings of grid environments requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. We developed an information system, based on collaborative agents, that supports system administrators in monitoring the grid. While observing log files, the agents learn traffic patterns in their own local domain of the grid. The agents represent their knowledge in the form of deterministic finite automata (DFA), and share their models to provide global or multi-domain overviews. We discuss our collaborative learning mechanism and show the results of our experiments with data of two grid-sites. Our system generated jobtraffic overviews that gave new insights in the performance of the grid environment.

In distributed service oriented ICT environments, where broker components control and delegate th... more In distributed service oriented ICT environments, where broker components control and delegate the work to appropriate services, the value of information that these brokers use in their mechanisms is found to be prone to the dynamics of the infrastructure. In this paper we describe our research on anticipating brokers that make use of predictive information services. We start with a

In-vehicle information management is vital in intelligent traffic systems. In this paper we motiv... more In-vehicle information management is vital in intelligent traffic systems. In this paper we motivate an architecture for ontology-based context-aware reasoning for in-vehicle information management. Ontology- based reasoning allows context-awareness, inference and advanced reasoning capabilities. However, the amount of computational power it requires often conflicts with the computational limitations of on-board units, as well as the high demand for timeliness and safety. Our approach uses ontology-based reasoning and a finite state machine (FSM). By combining ontology and FSM, we illustrate how a heavy-weight reasoning-solution could be applied in a light-weight computational environment.

ABSTRACT This paper proposes a distributed learning mechanism that learns patterns from distribut... more ABSTRACT This paper proposes a distributed learning mechanism that learns patterns from distributed datasets. The complex and dynamic settings of grid environments requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. We developed an information system, based on collaborative agents, that supports system administrators in monitoring the grid. While observing log files, the agents learn traffic patterns in their own local domain of the grid. The agents represent their knowledge in the form of deterministic finite automata (DFA), and share their models to provide global or multi-domain overviews. We discuss our collaborative learning mechanism and show the results of our experiments with data of two grid-sites. Our system generated job-traffic overviews that gave new insights in the performance of the grid environment.

Lecture Notes in Computer Science, 2008

Service oriented systems need to be maintained to keep the requested level of service. This is ch... more Service oriented systems need to be maintained to keep the requested level of service. This is challenge in large grid-and saas based networks that are managed by numerous entities. This paper is about supporting multi agent systems that operate in the network and support its management by learning actual structures from life observed logging data. We focus on a collaborative grammar induction mechanism in which agents share local models in order to retrieve a model of the structure of the total service network. We studied the performance of groups of agents while varying the size and degree of communication. We motivate the application of the mechanism in the domain of service oriented system and show the results of experiments using a distributed agent-based monitoring system. We promote further research in the overlapping scientific disciplines of multi agent systems and machine learning in the application domain of service oriented systems.

Lecture Notes in Computer Science, 2013

ABSTRACT Grid monitoring requires analysis of large amounts of log files across multiple domains.... more ABSTRACT Grid monitoring requires analysis of large amounts of log files across multiple domains. An approach is described for automated extraction of job-flow information from large computer grids, using software agents and genetic computation. A prototype was created as a first step towards communities of agents that will collaborate to learn log-file structures and exchange knowledge across organizational domains.

Lecture Notes in Computer Science, 2010

ABSTRACT We introduce a formal paradigm to study global adaptive behavior of organizations of col... more ABSTRACT We introduce a formal paradigm to study global adaptive behavior of organizations of collaborative agents with local learning capabilities. Our model is based on an extension of the classical language learning setting in which a teacher provides examples to a student that must guess a correct grammar. In our model the teacher is transformed in to a workload dispatcher and the student is replaced by an organization of worker-agents. The jobs that the dispatcher creates consist of sequences of tasks that can be modeled as sentences of a language. The agents in the organization have language learning capabilities that can be used to learn local work-distribution strategies. In this context one can study the conditions under which the organization can adapt itself to structural pressure from an environment. We show that local learning capabilities contribute to global performance improvements. We have implemented our theoretical framework in a workbench that can be used to run simulations. We discuss some results of these simulations. We believe that this approach provides a viable framework to study processes of self-organization and optimization of collaborative agent networks.

Methods and Tools for Collaborative Networked Organizations, 2008

IFIP International Federation for Information Processing, 2004

This paper addresses the area of software development and maintenance for GRID- based application... more This paper addresses the area of software development and maintenance for GRID- based applications. We argue that the structure and geographical spread of these systems poses new challenges to the ICT services industry. We believe that human intelligence and related skills are a central element in facing these challenges and see the emerging paradigm of virtual organizations as promising direction

Lecture Notes in Computer Science, 2010

ABSTRACT We show that within the Gold paradigm for language learning an informer for a superfinit... more ABSTRACT We show that within the Gold paradigm for language learning an informer for a superfinite set can cause an optimal MDL learner to make an infinite amount of mind changes. In this setting an optimal learner can make an infinite amount of wrong choices without approximating the right solution. This result helps us to understand the relation between MDL and identification in the limit in learning: MDL is an optimal model selection paradigm, identification in the limit defines recursion theoretical conditions for convergence of a learner.

Methods and Tools for Collaborative Networked Organizations, 2008

Lecture Notes in Computer Science, 2007

In e-Science, scientific workflow systems are used to share data and knowledge in collaborative e... more In e-Science, scientific workflow systems are used to share data and knowledge in collaborative experiments. In recent work we discussed the concepts of a workflow bus [1], allowing multiple workflow systems to be coupled in a meta-workflow system with multiple execution models. In this paper we propose an approach for a formal model to perform the task of reasoning of about the execution models of such workflow systems. We show that I/O Automata can be used as a formalism to prove the correctness of complicated workflows involving multiple workflow engines and execution models.

Proceedings of the 6th international conference industry session on Grids meets autonomic computing - GMAC '09, 2009

The complex and dynamic settings of grid environments lead to challenges on their operational mai... more The complex and dynamic settings of grid environments lead to challenges on their operational maintenance. The growth of these environments in terms of size and usage requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. Communication across organizational domains and interoperability between existing monitoring tools is subject to improvement. In this paper we present an information system, based on collaborative agents, that supports system administrators in monitoring the grid. While observing log files, the agents learn patterns about job-traffic in their own local domain of the grid and share information to provide global or multi-domain overviews. The agents represent their knowledge in the form of deterministic finite automata (DFA). We discuss our collaborative learning mechanism and show the results of our experiments with data of two grid-sites. Our system generated job-traffic overviews that gave new insights in the performance of the grid environment.

GEOPHYSICS, 2008

We modeled time-domain EM measurements of induction currents for marine and land applications wit... more We modeled time-domain EM measurements of induction currents for marine and land applications with a frequencydomain code.An analysis of the computational complexity of a number of numerical methods shows that frequency-domain modeling followed by a Fourier transform is an attractive choice if a sufficiently powerful solver is available. A recently developed, robust multigrid solver meets this requirement. An interpolation criterion determined the automatic selection of frequencies. The skin depth controlled the construction of the computational grid at each frequency. Tests of the method against exact solutions for some simple problems and a realistic marine example demonstrate that a limited number of frequencies suffice to provide time-domain solutions after piecewise-cubic Hermite interpolation and a fast Fourier transform.

Network-Centric Collaboration and Supporting …, 2006

Information retrieval is one of the key processes in the management of collaborative networks (CN... more Information retrieval is one of the key processes in the management of collaborative networks (CNs). For large and complex networks manual processes need to be supported by automated retrieval systems. We study the characteristics of information retrieval ...