A QoS-Control Architecture for Object Middleware

This paper presents an architecture for QoS-aware middleware platforms. We present a general framework for control, and specialise this framework for QoS provisioning in the middleware context. We identify different alternatives for control, and we elaborate the technical issues related to controlling the internal characteristics of object middleware. We illustrate our QoS control approach by means of a scenario based on CORBA

Educational use cases from a shared exploration of e-books and iPads

E-books and e-book readers are becoming increasingly widely available, particularly for the general reader, and there have been many studies on their adoption. However, less is known about their use for educational and academic purposes. We report here on work carried out on e-books and e-book applications using iPads by academic and teaching staff. After considering pedagogical issues and reporting survey results, we identify a spiral of six key use case areas for e-books. This spiral of use cases moves from basic e-book use, through situational reading, e-books and learning, using multiple learning resources, collaborative/group learning, to e-book production. We discuss each of these use case areas and provide guidelines that will be of interest to practitioners and researchers alike

METAPLEX: AN INTEGRATED ENVIRONMENT FOR ORGANIZATION AND INFORMATION SYSTEMS DEVELOPMENT

This paper presents an integrated environment, called MetaPlex; for organization and information systems development. The kernel of MetaPlex is a knowledge base management system which captures the semantic primitives of a domain at the meta level and uses these primitives to describe target systems. Three levels of abstraction are used in MetaPlex for representing knowledge: the axiomatic, median, and instance levels. The MetaPlex Language Definition System is used to name the object types in the domain of interest and to define the attributes, relations, and descriptions which can be used by these object types. The structural knowledge of the domain in general is thus captured at the median level. Knowledge of the domain captured at the median level is used by the MetaPlex Specification System to define a target system at the instance level. A rule-based inference engine is embedded in the MetaPlex environment as an intelligent assistant to help end users. The expertise of a designer can be codified into a rule set which can assist users in classifying an object, in decomposing a high level system component, or in clustering the detailed components at the lower level. Both topdown and bottom-up approaches for systems development are thus supported. A layered approach has been proposed to manage the dynamics of such a metasystem environment. An enterprise model has been developed to demonstrate the usage of MetaPlex and the integration of organization and information systems modeling. Directions for future research are also discussed

Expert-System Shells : Very-High-Level Languages for Artificial Intelligence

Expert-system shells are discussed as very-high-level programming languages for knowledge engineering. Based on a category/domain distinction for expert systems the concept of expert-system shells is explained using seven classifications. A proposal for a shell-development policy is sketched. The conclusions express concern about overemphasis on shell surfaces

A Risk- and Fuzzy Set-Based Methodology for Advanced Concept Technology Demonstration Military Utility Assessment Design

The U.S. Department of Defense Advanced Concept Technology Demonstration (ACTD) and derivative, rapid acquisition programs offer timely solutions to critical military needs by assessing the utility of technologies mature enough to be fielded without application of traditional, defense system development processes. Military utility assessments (MUA) are ACTDs\u27 most critical features, but the lack of a standard for identifying assessment criteria tailored to specific demonstrations risks poorly informed acquisition decisions and the military operations those decisions are intended to support. The purpose of this research was to develop and deploy a methodology for identifying measures of effectiveness integral to advanced concept technology demonstration military utility assessment design. Within a context determined by attributes of complex systems, the research observed twin premises that ACTD assessment designs should accommodate: all risks possible when incorporating demonstration prototypes within superior and complex, joint military operations metasystems; and the ambiguities and other of what have been termed “fuzzy” manifestations of the cognition and language with which end-user, military operators craft and express perspectives required to identify measures of effectiveness fundamental to MUA designs. The effort pursued three research questions: (1) How might joint military operations metasystem models guide the identification of ACTD measures of effectiveness? (2) How might be developed and employed joint military metasystem models with which can be identified ACTD measures of effectiveness? (3) How useful might ACTD managers and analysts find the MUA design methodology developed and deployed with this research? The deployed methodology stimulated answers to these research questions by uniquely combining tailored versions of established risk assessment methods with a fuzzy method for resolving small group preferences. The risk assessment methods honored one research premise while enabling the identification and employment of a joint military operations metasystem model suited to MUA design needs of a simulated ACTD. The fuzzy preference method honored the second research premise as it, too, promoted metasystem model employment. The complete methodology was shown to hold favor with a large segment of a community expert in managing and assessing the utility of ACTDs emphasizing critical, joint military service needs

Differential games through viability theory : old and recent results.

This article is devoted to a survey of results for differential games obtained through Viability Theory. We recall the basic theory for differential games (obtained in the 1990s), but we also give an overview of recent advances in the following areas : games with hard constraints, stochastic differential games, and hybrid differential games. We also discuss several applications.Game theory; Differential game; viability algorithm;

Inference engine in objectbase: a mean towards metasystems.

Yu-shan Chan.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 95-99).Chapter 1. --- INTRODUCTION --- p.1Chapter 1.1 --- "Expert System, Expert System Shell, and ""MetaSystem""" --- p.2Chapter 1.2 --- Adopting OBJECTBASE In EXPERT SYSTEM SHELL(ESS) --- p.4Chapter 2. --- SURVEY ON EXISTING SYSTEMS --- p.7Chapter 2.1 --- Review of inference models --- p.7Chapter 2.1.1 --- The Classical Period --- p.9Chapter 2.1.2 --- The modern period --- p.11Chapter 2.2 --- Rules in Objectbase vs. other Representations --- p.12Chapter 2.2.1 --- Rule-based systems --- p.13Chapter 2.2.2 --- Object-oriented systems --- p.13Chapter 2.2.3 --- Other systems --- p.13Chapter 2.2.4 --- Rules embedded in object-- the Objectbase approach --- p.14Chapter 2.3 --- Conclusion --- p.15Chapter 3. --- DESIGN OF ESS FOR AN OBJECTBASE SYSTEM --- p.16Chapter 3.1 --- Introducing ESS in Objectbase --- p.18Chapter 3.1.1 --- The Concept of Object Modeling --- p.19Chapter 3.1.2 --- Why Objectbase? --- p.20Chapter 3.1.3 --- ESS : a higher layer on Objectbase --- p.22Chapter 3.1.4 --- Schema Objects and Shell Objects --- p.23Chapter 3.2 --- Module design of ESS --- p.24Chapter 3.2.1 --- Knowledge Representation Module --- p.25Chapter 3.2.2 --- Objectbase inference module --- p.27Chapter 3.2.3 --- The Rule一Inference Module --- p.28Chapter 3.3 --- Knowledge Representation --- p.29Chapter 3.3.1 --- Schema Knowledge & the Rulebase --- p.30Chapter 3.3.2 --- Rule Structure --- p.31Chapter 3.4 --- Inference Engine --- p.35Chapter 3.4.1 --- The Two Levels of Inference --- p.35Chapter 3.5 --- Rule一Inference (RI) --- p.37Chapter 3.5.1 --- Structural design of RI --- p.38Chapter 3.5.2 --- Drawing Inference --- p.39Chapter 3.5.3 --- Query Processor and RI --- p.42Chapter 3.5.4 --- RI and the Inference Engine(IE) --- p.43Chapter 3.6 --- Conclusion --- p.43Chapter 4. --- IMPLEMENTATION --- p.45Chapter 4.1 --- Rulelnference: a comprehensive structure --- p.46Chapter 4.1.1 --- Class Rule --- p.46Chapter 4.1.2 --- Class RuleList --- p.47Chapter 4.1.3 --- Accompany data structures for inference --- p.48Chapter 4.1.4 --- Class Rulelnference --- p.49Chapter 4.2 --- Rule Setting --- p.51Chapter 4.2.1 --- Rule Construction --- p.51Chapter 4.2.2 --- Rule Parsing and the Rule Definition Language (RDL) --- p.52Chapter 4.3 --- How Inference is done in ESS --- p.53Chapter 4.3.1 --- Reset and Load system --- p.53Chapter 4.3.2 --- Inference making --- p.54Chapter 4.4 --- Using RuleInference in the Rule Constructor --- p.58Chapter 4.4.1 --- The Rule Constructor --- p.59Chapter 4.5 --- Using Rulelnference in the Application Constructor --- p.60Chapter 4.5.1 --- The RiNode --- p.61Chapter 4.5.2 --- Schema and Rule Set Handling --- p.63Chapter 4.6 --- Conclusion --- p.64Chapter 5. --- CASE STUDY --- p.66Chapter 5.1 --- Background on Statement analysis --- p.66Chapter 5.1.1 --- Ratios for decision making --- p.68Chapter 5.2 --- Sample System: Financial Data Analysis System --- p.70Chapter 5.2.1 --- The FINANCE schema --- p.71Chapter 5.2.2 --- Rules --- p.73Chapter 5.2.3 --- Results --- p.75Chapter 5.3 --- Evaluation --- p.81Chapter 5.4 --- Conclusion --- p.82Chapter 6. --- RESULT AND DISCUSSION --- p.84Chapter 6.1 --- An Expert System Shell on Objectbase --- p.84Chapter 6.2 --- The ESS on MOBILE --- p.85Chapter 6.3 --- Pros and cons for the ESS --- p.86Chapter 6.4 --- MOBILE: how it has been improved --- p.87Chapter 7. --- CONCLUSION --- p.89Chapter 7.1 --- Comparison --- p.91Chapter 7.2 --- Appraisal --- p.92Chapter 8. --- REFERENCES --- p.95Table of Content for AppendixesAPPENDIX 1. RULE DEFINITION LANGUAGE --- p.100APPENDIX 2. THE CLASS RULEINFERENCE --- p.103APPENDIX 3. THE RINODE --- p.104APPENDIX 4. FINANCIAL STATEMENT ANALYSIS --- p.108APPENDIX 5. DATA STRUCTURE OF RULE AND RULELIST --- p.117APPENDIX 6. DATA STRUCTURE OF VARLIST AND ACTLIST --- p.118APPENDIX 7. DATA STRUCTURE OF RULEINFERENCE --- p.12

ANALOGICAL AND DEPENDENCY DIRECTED REASONING STRATEGIES FOR LARGE SYSTEMS EVOLUTION

The maintenance of large information systems involves continuous design modifications to designs in response to evolving business conditions or changing user requirements. Because of the complexity barrier associated with engineering such systems, changes can be ad hoc and prone to errors. Based on our observations of such a process in the oil industry, we believe that the systems maintenance activity would benefit greatly if the process knowledge reflecting the teleology of a design could be captured and used in order to reason about changing requirements, and to design parts of systems that might be âsimilarâ to existing ones. In this paper, we describe a partially implemented formalism called REMAP (REpresentation and MAintenance of Process knowledge) that accumulates design process knowledge to manage systems evolution. To accomplish this, REMAP acquires and maintains dependencies among the design decisions made during a prototyping process as well as the general domain-specific design rules on which such dependencies are based. This knowledge can then be applied to prototype refinement, systems maintenance, and the re-use of existing designs to construct âsimilarâ design fragments.Information Systems Working Papers Serie

Morphometrics of Southern Ocean diatoms using high throughput imaging and semi-automated image analysis

Since the ADIAC project, which ended more than 15 years ago, not much progress in automating morphometric analysis of diatoms from slide-mounted material has been published, and no ready-to-use system has become available. This thesis work is the first to implement such a system completely, covering all aspects of the underlying imaging and image processing pipeline, by combining a commercially available slide scanning microscope with my diatom morphometry software SHERPA. I was able to show the applicability as well as the potential of this approach by executing a series of smaller and two large-scale morphometry projects. The extensive sampling sizes, which were made possible only by the new workflow, enabled the first observations of life cycle related size distribution changes of Fragilariopsis kerguelensis in its natural habitat, leading to hypotheses on influences of reproduction, grazing and environmental changes in one of the most important diatom species of the Southern Ocean. In a second large-scale investigation, SHERPA's precise morphometric measurements revealed a second F. kerguelensis morphotype, which has not been recognized before, even though the species, as well as the very material I analyzed, have been investigated intensely before by experienced diatomists; a result not disqualifying their work, but rather underlining that explicit and precise quantification of morphological information has a strong potential to generate novel scientific insights. This new morphotype has implications on the utilization of paleo-proxies which are based on geometrical valve features of F. kerguelensis. Differentiating both morphotypes might improve established methods and possibly provides a new proxy for summer sea surface temperature

Learning-Assisted Automated Reasoning with Flyspeck

The considerable mathematical knowledge encoded by the Flyspeck project is combined with external automated theorem provers (ATPs) and machine-learning premise selection methods trained on the proofs, producing an AI system capable of answering a wide range of mathematical queries automatically. The performance of this architecture is evaluated in a bootstrapping scenario emulating the development of Flyspeck from axioms to the last theorem, each time using only the previous theorems and proofs. It is shown that 39% of the 14185 theorems could be proved in a push-button mode (without any high-level advice and user interaction) in 30 seconds of real time on a fourteen-CPU workstation. The necessary work involves: (i) an implementation of sound translations of the HOL Light logic to ATP formalisms: untyped first-order, polymorphic typed first-order, and typed higher-order, (ii) export of the dependency information from HOL Light and ATP proofs for the machine learners, and (iii) choice of suitable representations and methods for learning from previous proofs, and their integration as advisors with HOL Light. This work is described and discussed here, and an initial analysis of the body of proofs that were found fully automatically is provided