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Software Engineering for Ensembles ⋆
"... Abstract. Software development is difficult, even if we control most of the operational parameters and if the software is designed to run on a single machine. But in the future we will face an even more challenging task: engineering ensembles consisting of thousands, or even millions, of nodes, all ..."
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Abstract. Software development is difficult, even if we control most of the operational parameters and if the software is designed to run on a single machine. But in the future we will face an even more challenging task: engineering ensembles consisting of thousands, or even millions, of nodes, all operating in parallel, with open boundaries, possibly unreliable components and network links, and governed by multiple entities. To develop reliable and trustworthy software for these kinds of systems we need to go far beyond the current state of the art and address fundamental problems in software development. We present some challenges and promising avenues for research about software-engineering for ensembles. 1
Causality in Databases: The Diagnosis and Repair Connections
- Proc. 15th International Workshop on Non-Monotonic Reasoning (NMR 2014). Corr Arkiv Paper cs.DB/1404.6857
, 2014
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From Modelica Models to Fault Diagnosis in Air Handling Units
"... Abstract This paper presents a methodology for model-based fault detection and diagnosis underpinned by modelica models and using a qualitative approach to diagnosis, which has been applied to diagnosis of an air handling unit based on data recorded by a building management system. The main steps f ..."
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Abstract This paper presents a methodology for model-based fault detection and diagnosis underpinned by modelica models and using a qualitative approach to diagnosis, which has been applied to diagnosis of an air handling unit based on data recorded by a building management system. The main steps from model development to component diagnosis are discussed and illustrated using a heating coil component.
Machine-Learning-Based Circuit Synthesis Anonymous
"... Abstract—Multi-level logic synthesis is a problem of immense practical significance, and is a key to developing circuits that optimize a number of parameters, such as depth, energy dissipation, reliability, etc. The problem can be defined as the task of taking a collection of components from which o ..."
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Abstract—Multi-level logic synthesis is a problem of immense practical significance, and is a key to developing circuits that optimize a number of parameters, such as depth, energy dissipation, reliability, etc. The problem can be defined as the task of taking a collection of components from which one wants to synthesize a circuit that optimizes a particular objective function. This problem is computationally hard, and there are very few automated approaches for its solution. To solve this problem we propose an algorithm, called Circuit-Decomposition Engine (CDE), that is based on learning decision trees, and uses a greedy approach for function learning. We empirically demonstrate that CDE, when given a library of different component types, can learn the function of Disjunctive Normal Form (DNF) Boolean representations and synthesize circuit structure using the input library. We compare the structure of the synthesized circuits with that of well-known circuits using a range of circuit similarity metrics. I.
2012 IEEE 27-th Convention of Electrical and Electronics Engineers in Israel Machine-Learning-Based Circuit Synthesis
"... Abstract—Multi-level logic synthesis is a problem of immense practical significance, and is a key to developing circuits that optimize a number of parameters, such as depth, energy dissi-pation, reliability, etc. The problem can be defined as the task of taking a collection of components from which ..."
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Abstract—Multi-level logic synthesis is a problem of immense practical significance, and is a key to developing circuits that optimize a number of parameters, such as depth, energy dissi-pation, reliability, etc. The problem can be defined as the task of taking a collection of components from which one wants to synthesize a circuit that optimizes a particular objective function. This problem is computationally hard, and there are very few automated approaches for its solution. To solve this problem we propose an algorithm, called Circuit-Decomposition Engine (CDE), that is based on learning decision trees, and uses a greedy approach for function learning. We empirically demonstrate that CDE, when given a library of different component types, can learn the function of Disjunctive Normal Form (DNF) Boolean representations and synthesize circuit structure using the input library. We compare the structure of the synthesized circuits with that of well-known circuits using a range of circuit similarity metrics. I.
Modeling for Fault Localization in Data Warehouse Applications
"... The paper describes first results of an attempt to develop a general tool for localizing faults in applications of data warehouse technology. Genericity is achieved by a model-based approach: a model of the application is configured from a library of models of standard (types of) modules and exploit ..."
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The paper describes first results of an attempt to develop a general tool for localizing faults in applications of data warehouse technology. Genericity is achieved by a model-based approach: a model of the application is configured from a library of models of standard (types of) modules and exploited by a consistency-based diagnosis algorithm, originally used for diagnosing physical devices. In order to obtain discriminating interdependencies, the behavior description in the models is stratified according to different roles and processing of the various types of the data and captures the potential impact of faults of process steps and data transfer on the data as well as on sets of data. Reflecting the nature of the initial symptoms and of the potential checks, these descriptions are stated at a qualitative level. In the current solution, the symptoms are assumed to stem from human assessment of reports generated from the data ware house, while checks can be inspection of the data base or other persistent data and rerunning certain process steps. The solution has been validated in customer report generation of a provider of mobile phone services. 1.
Debugging Support for Data Warehouse Applications
"... The paper describes a model-based approach to developing a general tool for localizing faults in applications of data warehouse technology. A model of the application is configured from a library of generic models of standard (types of) modules and exploited by a consistency-based diagnosis algorith ..."
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The paper describes a model-based approach to developing a general tool for localizing faults in applications of data warehouse technology. A model of the application is configured from a library of generic models of standard (types of) modules and exploited by a consistency-based diagnosis algorithm, originally used for diagnosing physical devices. Observing intermediate results can require high efforts or even be impossible, which limits the discriminability between different faults in a sequence of data processing steps. To compensate for this, fault models are used. This becomes a feasible solution for standard modules of a data warehouse application along with a stratification of the data. Fault models capture the potential impact of faults of process steps and data transfer on the data strata as well as on sets of data. Reflecting the nature of the initial symptoms and of the potential checks, these descriptions are stated at a qualitative level. The solution has been validated in customer report generation of a provider of mobile phone services.
Second Annual Conference on Advances in Cognitive Systems Poster Collection (2013) 77-92 An Expectations Framework for Domestic Robot Assistants
"... Robots that are supposed to work in everyday environments are confronted with a wide variety of situations. Not all such situations can be taken into account by a programmer when implementing the system. This is why robots often show strange behavior when they encounter situations that their program ..."
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Robots that are supposed to work in everyday environments are confronted with a wide variety of situations. Not all such situations can be taken into account by a programmer when implementing the system. This is why robots often show strange behavior when they encounter situations that their programmer has not expected. We propose a knowledge-based approach to explicitly represent expectations in the robot program. Comparing those expectations to the current situation allows the robot itself to detect unusual situations and react appropriately. Our general framework can incorporate expectations from different knowledge sources and offers a flexible combination of different expectations. We demonstrate the feasibility of the approach in the context of a household robot in simulation and in a real environment. Finally we discuss the adequacy of our proposed solution and open questions for further research. 1.
Diagnosis of Bottling Plants – First Success and Challenges
"... Abstract: The paper describes an application of component-oriented consistency-based diagnosis to the domain of bottle-filling plants. The task is to localize the causes for stops of the central aggregate, the filler, based on recorded operation data of a plant. A model-based solution is challenging ..."
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Abstract: The paper describes an application of component-oriented consistency-based diagnosis to the domain of bottle-filling plants. The task is to localize the causes for stops of the central aggregate, the filler, based on recorded operation data of a plant. A model-based solution is challenging in several respects, especially due to high uncertainty in the transportation processes to be modeled, the nature of the available data, and the relevance of numerical temporal information. We give a short description of the application and its requirements and summarize essential characteristics of the solution. We focus on the evaluation of the first demonstrator and a discussion of some challenges for future work, which include questioning the “classical ” notion of a fault in component-oriented diagnosis. 1.
