KSNet-Approach to Knowledge Fusion from Distributed Sources

The rapidity of the decision making process is an important factor in different branches of the human life (business, healthcare, industry, military applications etc.). Since responsible persons make decisions using available knowledge, it is important for knowledge management systems to deliver necessary and timely information. Knowledge logistics is a new direction in the knowledge management addressing this. Technology of knowledge fusion, based on the synergistic use of knowledge from multiple distributed sources, is a basis for these activities. The paper presents an overview of a Knowledge Source Network configuration approach (KSNet-approach) to knowledge fusion, multi-agent architecture and research prototype of the KSNet knowledge fusion system based on this approach

Microscopic modelling of the flow properties of polymers

The understanding of the flow behaviour of polymeric liquids is of great interest from a practical as well as a theoretical point of view. An important part of the research in this field consists of the development of suitable models, describing the rheological properties of the materials. Depending upon its purpose, such a model may be based upon empirical knowledge of the macroscopic flow behaviour or on information about the microstructure of the materials. Moreover, for a given system, different types of modelling may be possible. In order to provide an overview of the various approaches in this area the basic principles of some important models are discussed: continuum, bead-rod-spring, transient network, reptation and configuration tensor models. Emphasis has been put on a consistent treatment of the fundamentals of the various models and their interrelationship, rather than considering any of them in much detail

The application of knowledge based systems to the abstraction of design and costing rules in bespoke pipe jointing systems

This thesis presents the work undertaken in the creation of a knowledge based system aimed at facilitating the design and cost estimation of bespoke pipe jointing systems. An overview of the problem domain is provided and the findings from a literature review on knowledge based systems and applications in manufacturing were used to provide initial guidance to the research. The overall investigation and development process involved the abstraction of design and costing rules from domain experts using a sub-set of the techniques reviewed and the development and implementation of the knowledge based system using an expert system approach, the soft systems methodology (SSM) and the system development lifecycle methodology. Based on the abstracted design and costing rules, the developed system automates the design of pipe jointing systems, and facilitates cost estimation process within third party configuration software. The developed system was validated using two case studies and was shown to provide the required outputs

Configuring a machining operation as a Constraint Satisfaction Problem

International audienceThe problem of configuring a machining operation is complex (many parameters and many interactions between parameters) and is generally achieved thanks to expert heuristic knowledge. Indeed, the configuration of a machining operation is often carried out according to a specific procedure: choice of a kind of operation and of a kind of machine, then choice of a set of tools and at the end selection of cutting conditions. We propose in this paper a general framework for the configuration of a machining operation based on a constraint representation and manipulation. We first present a model of the decision variables (such as the machine, the tool, the insert or the feed rate), the non-decision variable and the constraints between variables. An overview of the 32 identified constraints is given in the paper. Even though it is not exhaustive, the basic constraints of the domain are represented. A typology of the constraints to be manipulated is then given leading order to a specification of algorithms for search and consistency checking that may allow to manage these kinds of constraints

A mathematical programming model for air traffic flow management with dynamic selection of the airspace configuration

In this thesis we present a new integer linear programming model for air traffic flow management. The goal of the model is to minimize the cost of flight delays. The introduction provides an overview of the air traffic flow management problem. The problem is addressed through a combination of actions such as ground-holding, airborne-holding, speed control and choice of the most appropriate configuration of the airspace. The configuration may be changed over time, so that the last action implies dynamism of the airspace configuration and allows controllers to monitor the flow of traffic more effectively. Nevertheless, to the best of our knowledge, the model we present in this thesis is the first one that exploits the use of dynamic airspace configurations. The new model is based on Integer Linear Programming formulation and it is compared to one state-of-the-art formulation using a single fixed configuration. Different model parameter settings are analysed, showing significant improvement in terms of reduced delays and related costs. Furthermore, theoretical considerations regarding the study of the linear relaxation of the new model are described. Finally, implementation details are provided

Ontology-based assistance system for control process reconfiguration of Robot-Based Applications

Due to increasing global competition, companies are challenged to make their production flexible and adaptable. This leads to a steadily increasing complexity of production systems and thus their automation and control processes. At the same time, control processes must be quickly configurable in order to be able to react to short product life cycles. Robot-based adhesive application in automotive body assembly represents one such control and automation process. In car body assembly, industrial robots are increasingly being used for gluing side panels, enabling flow operation in assembly. In the event of a functional change in the production process, such as the replacement of the adhesive to be used, all the given process interrelationships must be analysed again and reconfigured if necessary in order to ensure the quality of the bonded joint. Comprehensive data management systems that provide an overview of all the system parameters and control levers are often not available in companies, so that reconfiguration is based on experience. Correct adjustment of the process parameters thus requires the user to have precise knowledge of the complex interrelationships between the process and bonding parameters, which makes the search for solutions in the event of a process change more difficult and time-consuming. In order to master the complexity of process planning and configuration, a large number of user-supporting solutions exist in the area of product lifecycle management (PLM). However, these neither have the functionality to generate solution and optimization proposals, nor do they map the existing expert knowledge with so-called empirical values about the system behaviour. The advantages of semantic technologies including ontologies, such as their graph structure and suitability for the use of optimization algorithms, illustrate their potential as the basis of a knowledge-based assistance solution. Against this background, the aim of this paper is to develop an ontology-based knowledge management system that can consolidate existing product and process information and add expert knowledge to it. The resulting knowledge graph of the process is then examined using selected optimization algorithms (PMS, Parallel Machine Scheduling). From the analysis, configuration suggestions can be derived, which can be presented to the user with a visualisation interface. Finally, the potential of ontologies as the basis of a knowledge-based assistance system is evaluated based on given results

The student as producer: reinventing the student experience in higher education

In this chapter, we set out to provide an overview of recent critical responses to the corporatisation of higher education and the configuration of the student as consumer. We also discuss the relationship between the core activities of teaching and research and reflect on both nineteenth century discourse and more recent efforts to re-establish the university as a liberal humanist institution, where teaching and research are equal and fundamental aspects of academic life. While recognizing recent efforts which acknowledge and go some way to addressing the need for enquiry-based learning and constructivist models of student participation, we argue that a more critical approach is necessary to promote change at an institutional level. This critical approach looks at the wider social, political and economic context beyond the institution and introduces the work of Benjamin and other Marxist writers who have argued that a critique of the social relations of capitalist production is central to understanding and remodeling the role of the university and the relationship between academic and student. The idea of student as producer encourages the development of collaborative relations between student and academic for the production of knowledge. However, if this idea is to connect to the project of refashioning in fundamental ways the nature of the university, then further attention needs to be paid to the framework by which the student as producer contributes towards mass intellectuality. This requires academics and students to do more than simply redesign their curricula, but go further and redesign the organizing principle, (i.e. private property and wage labour), through which academic knowledge is currently being produced. An exemplar alternative organizing principle is already proliferating in universities in the form of open, networked collaborative initiatives which are not intrinsically anti-capital but, fundamentally, ensure the free and creative use of research materials. Initiatives such as Science Commons, Open Knowledge and Open Access, are attempts by academics and others to lever the Internet to ensure that research output is free to use, re-use and distribute without legal, social or technological restriction (www.opendefinition.org). Through these efforts, the organizing principle is being redressed creating a teaching, learning and research environment which promotes the values of openness and creativity, engenders equity among academics and students and thereby offers an opportunity to reconstruct the student as producer and academic as collaborator. In an environment where knowledge is free, the roles of the educator and the institution necessarily change. The educator is no longer a delivery vehicle and the institution becomes a landscape for the production and construction of a mass intellect in commons

Transfer Learning for Improving Model Predictions in Highly Configurable Software

Modern software systems are built to be used in dynamic environments using configuration capabilities to adapt to changes and external uncertainties. In a self-adaptation context, we are often interested in reasoning about the performance of the systems under different configurations. Usually, we learn a black-box model based on real measurements to predict the performance of the system given a specific configuration. However, as modern systems become more complex, there are many configuration parameters that may interact and we end up learning an exponentially large configuration space. Naturally, this does not scale when relying on real measurements in the actual changing environment. We propose a different solution: Instead of taking the measurements from the real system, we learn the model using samples from other sources, such as simulators that approximate performance of the real system at low cost. We define a cost model that transform the traditional view of model learning into a multi-objective problem that not only takes into account model accuracy but also measurements effort as well. We evaluate our cost-aware transfer learning solution using real-world configurable software including (i) a robotic system, (ii) 3 different stream processing applications, and (iii) a NoSQL database system. The experimental results demonstrate that our approach can achieve (a) a high prediction accuracy, as well as (b) a high model reliability.Comment: To be published in the proceedings of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'17