Software engineering for self-adaptive systems:a research roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and to identify critical challenges for the systematic software engineering of self-adaptive systems. The paper is partitioned into four parts, one for each of the identified essential views of self-adaptation: modelling dimensions, requirements, engineering, and assurances. For each view, we present the state-of-the-art and the challenges that our community must address. This roadmap paper is a result of the Dagstuhl Seminar 08031 on "Software Engineering for Self-Adaptive Systems," which took place in January 2008. © 2009 Springer Berlin Heidelberg.

Automatically Extracting Procedural Knowledge from Instructional Texts using Natural Language Processing

Procedural knowledge is the knowledge required to perform certain tasks, and forms an important part of expertise. A major source of procedural knowledge is natural language instructions. While these readable instructions have been useful learning resources for human, they are not interpretable by machines. Automatically acquiring procedural knowledge in machine interpretable formats from instructions has become an increasingly popular research topic due to their potential applications in process automation. However, it has been insufficiently addressed. This paper presents an approach and an implemented system to assist users to automatically acquire procedural knowledge in structured forms from instructions. We introduce a generic semantic representation of procedures for analysing instructions, using which natural language techniques are applied to automatically extract structured procedures from instructions. The method is evaluated in three domains to justify the generality of the proposed semantic representation as well as the effectiveness of the implemented automatic system.

Reconfiguration of supply chain network:an ISM-based roadmap to performance

Purpose: Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network. Design/methodology/approach: The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network. Findings: The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC. Practical implications: ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings. Originality/value: The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM. © Emerald Group Publishing Limited.

Self-adaptive probabilistic roadmap generation for intelligent virtual agents

Agents inhabiting large scale environments are faced with the problem of generating maps by which they can navigate. One solution to this problem is to use probabilistic roadmaps which rely on selecting and connecting a set of points that describe the interconnectivity of free space. However, the time required to generate these maps can be prohibitive, and agents do not typically know the environment in advance. In this paper we show that the optimal combination of different point selection methods used to create the map is dependent on the environment, no point selection method dominates. This motivates a novel self-adaptive approach for an agent to combine several point selection methods. The success rate of our approach is comparable to the state of the art and the generation cost is substantially reduced. Self-adaptation therefore enables a more efficient use of the agent's resources. Results are presented for both a set of archetypal scenarios and large scale virtual environments based in Second Life, representing real locations in London.

Measurement assisted assembly and the roadmap to part-to-part assembly

Cycle times and production costs remain high in aerospace assembly processes largely due to extensive reworking within the assembly jig. Other industries replaced these craft based processes with part-to-part assembly facilitated by interchangeable parts. Due to very demanding interface tolerances and large flexible components it has not been possible to achieve the required interchangeability tolerances for most aerospace structures. Measurement assisted assembly processes can however deliver many of the advantages of part-to-part assembly without requiring interchangeable parts. This paper reviews assembly concepts such as interface management, oneway assembly, interchangeability, part-to-part assembly, jigless assembly and determinate assembly. The relationship between these processes is then detailed and they are organized into a roadmap leading to part-to-part assembly.

A roadmap for cost engineering in the automotive supplier sector

The advent of global competition has introduced the need for new competitive manufacturing strategies. The implementation of new strategies has a dramatic effect on measuring product cost compared to traditional management accounting methods. It is found that new cost management methods are required to measure success and support decision-making within the new strategies. One example is the consequences of using traditional management accounting methods for measuring the effects of lean having catastrophic results during reporting. Such results steer managers away from lean manufacture based upon a false picture of the potential benefits. This research examines cost management methods potentially applicable within the automotive supplier sector. Because of the lack of cost-related data collected within the supplier sector companies, this paper ends with a demonstration of a novel method for use in data scarce environments. Copyright © 2008 Inderscience Enterprises Ltd.

Towards a 21st-century roadmap for biomedical research and drug discovery: consensus report and recommendations

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and nongovernmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathway-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this.