Combined Deep and Shallow Knowledge in a Unified Model for Diagnosis by Abduction

Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes-effects) but also deep knowledge (as structural / functional modularization and models on behavior). The paper proposes a unified approach on diagnosis by abduction based on plausibility and relevance criteria multiple applied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on target conductive flow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper gives hints on design and building of diagnosis system by abduction, embedding deep and shallow knowledge (according to case) and performing hierarchical fault isolation, along with a case study on a hydraulic installation in a rolling mill plant.Faulty Diagnosis, abduction, plausibility criteria, relevant criterion

Virtual infrastructure approach for SADU implementation

This paper proposes a new way of structuring the virtual infrastructure in terms of knowledge acquisition for SADU implementation. Through virtualization, the hardware infrastructure becomes a service, virtual machines become predominant within the infrastructure and their way of functioning can be affected by certain malfunctions. SADU supports human diagnostician in order to provide possible solutions to the raised issues. A virtualized IT infrastructure consists of layers that virtualized the used hardware components. Based on layers membership we propose a new approach to structuring the virtual infrastructure. This approach has fundamentally changed the architecture at the layer levels, increasing the security and availability of resources. Grouping layers depending on membership or type (hardware, virtual infrastructure, software) around the concept of stack led to a separation of intelligent agents’ responsibility for knowledge acquisition and fault diagnosis, allowing a better understanding of the field, reflected by developing a new ontology

Framework on Economical Implication and Issues of SADU Implementation

Due to software which plays an increasingly role in everyday life, interaction betweenhumans and computers will increase in importance; therefore, the ability to support interactions forefficient re-use of experience is a major challenge for systems in the future. Trace Based Reasoningwill have a significant impact on applications sharing experience, when they are based on the web inparticular, since traces allow us to imagine several ways of interaction in systems and to combinemultiple modes of interaction in a single system. In the conducted study we aimed at developing anAssist System of Human Diagnostician (SADU), meaning that this system will have the humanknowledge and then information retrieved by interaction with humans at the SADU request

COMBINED DEEP AND SHALLOW KNOWLEDGE IN A UNIFIED MODEL FOR DIAGNOSIS BY ABDUCTION

Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes-effects) but also deep knowledge (as structural / functional modularization and models on behavior). The paper proposes a unified approach on diagnosis by abduction based on plausibility and relevance criteria multiple applied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on target conductive flow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper gives hints on design and building of diagnosis system by abduction, embedding deep and shallow knowledge (according to case) and performing hierarchical fault isolation, along with a case study on a hydraulic installation in a rolling mill plant.shallow knowledge, diagnosis, flow systems

The Diagnosis by Abduction using Human Expert Knowledge

Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes-effects) but also deep knowledge (as structural / functional modularization and models on behavior). The paper proposes a unified approach on diagnosis by abduction based on plausibility and relevance criteria multiple applied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on target conductive flow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper gives hints on design and building of diagnosis system by abduction, embedding deep and shallow knowledge (according to case) and performing hierarchical fault isolation, along with a case study on a hydraulic installation in a rolling mill plant

Virtual reality-economical aspects in graphical illustration

The work presents the standard pattern centre -periphery, fundamented by Paul Krugman -1991. Based on the monopolistic competition Dixit-Stiglitz, it fundaments the economic agglomeration and is considered to be principal for the “new geographic economy“, a very fecund domain within the actual economic research. For the purpose of the presentation we have performed numeric simulations with the help of Maple product; the entire documentation is available for those concerned

Complex systems virtualization in the current’s economical context

How can we dramatically improve the efficiency and availability of resources and applications in our organization? Today, the answer is very simple: virtualization. Reducing your capital and IT operational costs by virtualizing your IT infrastructure in a „virtual infrastructure” while increasing the efficiency,utilization and flexibility of your existing assets. Go beyond server consolidation and deploy a standard virtualization platform to automate your entire IT infrastructure. Virtualization IT infrastructure delivers resources, applications and even servers when and where they are needed. Use the power of virtualization to better manage IT capacity, provide better service levels, and streamline IT processes. Respond to market dynamics faster and more efficiently than ever before with an automated virtualization platform

Combined deep and shallow knowledge in a unified model for diagnosis by abduction

Fault Diagnosis in real systems usually involves human expert’s shallow knowledge (as pattern causes-effects) but also deep knowledge (as structural / functional modularization and models on behavior). The paper proposes a unified approach on diagnosis by abduction based on plausibility and relevance criteria multiple applied, in a connectionist implementation. Then, it focuses elicitation of deep knowledge on target conductive flow systems – most encountered in industry and not only, in the aim of fault diagnosis. Finally, the paper gives hints on design and building of diagnosis system by abduction, embedding deep and shallow knowledge (according to case) and performing hierarchical fault isolation, along with a case study on a hydraulic installation in a rolling mill plant

Consulting in Electronic Commerce

Economic development of electronic services provide advice and many agents of existing referral systems to recommend and provide products, information and customized views of the community through a personalized interaction in real time. Distributed systems of autonomous agents are becoming increasingly important in electronic comet because the basic decisions of agents advice on trust and reputation are taken in a similar way human society. If these decisions will be like a real consumer protection, when new aspects of online consumer legislation will become useful information in advice and consulting of electronic commerce

Intelligent Agents in Knowledge Acquisition and Structuring for the Fault Diagnosis of Virtualized Systems

The knowledge acquisition concerning the behavior at the fault of the complex systems is a systematic process, first, by the presentation of the processes, procedures and stages that occur throughout of a acquisition project of knowledge. Also, a good knowledge of the system, with all its features, is a good decisive factor concerning the successful realization of the knowledge acquisition.In addition, for the fault diagnosis it is required the knowledge and the knowledge acquisition for thefault behavior (anomaly/symptoms and manifestations, granularity of the defects, relations betweenthem in various operating environments)