Neural networks applied to wireless communications

This paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a wireless transmitter.IFIP International Conference on Artificial Intelligence in Theory and Practice - Neural NetsRed de Universidades con Carreras en Informática (RedUNCI

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Modeling dynamic interactions in supply chains using agentbased simulations

In this work, we present preliminary results of our research on the construction of an agent-based simulation framework suitable to support the analysis of complex supply chain interactions as the one required for the performance assessment in collaborative supply chains. In particular we focus in the modeling of dynamic interactions through agent-to-agent message communication avoiding predefined supply chain network structures. For defining the internal structure of agents we explore the application of the SCOR reference model to bring a business process perspective and adopt the requirement of making explicit separation of the execution and control and decision making processes.Sociedad Argentina de Informática e Investigación Operativ

Modeling Transport in Service-Oriented Framework for Agent-Based Simulations of Supply Chains

This work presents an extension to the service-oriented framework for performing agent-based simulations to support the analysis of collaborative relationships in supply chain interactions already described in [5]. The extension includes a new service for simulating the planning of transportation, which is designed to allocate finite transportation resources to the transportation orders. The service includes the functionality that matches the required vehicle type, location and time to track the availability of a vehicle fleet as it is allocated to a plan. The new service proposal is validated by simulating three different scenarios of a case study. The case study is based on an actual supply chain of dairy products covering the central region of Argentina.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Data mining use for learning process design of an information source locator agent

The aim of this work is to present a data mining application to software engineering. We describe the use of data mining in some parts of the design process of a dynamic decision support system agent-based architecture. The main function of this system is to guide information requirements from users to the domains that offer greater possibilities of answering them. For that purpose, a strategy is developed, which provides the system with capacity for analyzing an information requirement, and determining to which domains it will be directed. To learn from errors made during its operation, a learning mechanism based in CBR techniques is also proposed. On the one hand, by using data mining techniques it is possible to define a discriminating function to classify the system domains into two groups: those that can probably provide an answer to the information requirement made to the system, and those that cannot. On the other hand, the application of data mining to the cases base allows the specification of rules to settle relationships among the stored cases with the aim of inferring possible causes of error in the domains classification. In this way, a learning mechanism is designed to update the knowledge base and thus improve the already made classification as regards the values assigned to the discriminating function.Eje: Aprendizaje y reconocimiento de patronesRed de Universidades con Carreras en Informática (RedUNCI

Verification of Structured Processes: A Method Based on an Unsoundness Profile

The verification of business processes has been widely studied in the last two decades achieving significant results. Despite this, existing verification techniques based on state space exploration suffer, for large processes, the state space explosion problem. New techniques improved verification performance by structuring processes as trees. However, they do not support complex constructs for advanced synchronization and exception management. To cope with this issue we propose the definition of an unsoundness profile of a given process language, which specifies all possible combinations of control flow constructs that can lead to errors in the behavior of structured processes defined with such a language. In addition, we introduce the sequential and hierarchical soundness properties, which make use of this profile to determine soundness of a structured process with complex constructs in polynomial time. As an example, we defined an unsoundness profile for a subset of the BPMN language and verified the behavior of a BPMN process model.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Modeling Transport in Service-Oriented Framework for Agent-Based Simulations of Supply Chains

This work presents an extension to the service-oriented framework for performing agent-based simulations to support the analysis of collaborative relationships in supply chain interactions already described in [5]. The extension includes a new service for simulating the planning of transportation, which is designed to allocate finite transportation resources to the transportation orders. The service includes the functionality that matches the required vehicle type, location and time to track the availability of a vehicle fleet as it is allocated to a plan. The new service proposal is validated by simulating three different scenarios of a case study. The case study is based on an actual supply chain of dairy products covering the central region of Argentina.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Detection of Anti-Patterns in the Control Flow of Collaborative Business Processes

The verification of the behavior of Collaborative Business Processes is an important aspect to consider when developing inter-organizational systems. In this work, a verification approach for the control flow of collaborative processes based on anti-patterns is proposed to improve the performance of verification. The approach supports the verification of complex constructs for advanced synchronization, multiple instances, and exception management. To this aim, 10 anti-patterns were defined from a repository of process models, and a tool which implements the anti-patterns was developed to evaluate the verification approach. Results indicate that, at worst, the verification time is less than half a millisecond, even for models with complex control flow constructs.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Detection of Anti-Patterns in the Control Flow of Collaborative Business Processes

The verification of the behavior of Collaborative Business Processes is an important aspect to consider when developing inter-organizational systems. In this work, a verification approach for the control flow of collaborative processes based on anti-patterns is proposed to improve the performance of verification. The approach supports the verification of complex constructs for advanced synchronization, multiple instances, and exception management. To this aim, 10 anti-patterns were defined from a repository of process models, and a tool which implements the anti-patterns was developed to evaluate the verification approach. Results indicate that, at worst, the verification time is less than half a millisecond, even for models with complex control flow constructs.Sociedad Argentina de Informática e Investigación Operativa (SADIO