The NeOn Methodology for Ontology Engineering

In contrast to other approaches that provide methodological guidance for ontology engineering, the NeOn Methodology does not prescribe a rigid workflow, but instead it suggests a variety of pathways for developing ontologies. The nine scenarios proposed in the methodology cover commonly occurring situations, for example, when available ontologies need to be re-engineered, aligned, modularized, localized to support different languages and cultures, and integrated with ontology design patterns and non-ontological resources, such as folksonomies or thesauri. In addition, the NeOn Methodology framework provides (a) a glossary of processes and activities involved in the development of ontologies, (b) two ontology life cycle models, and (c) a set of methodological guidelines for different processes and activities, which are described (a) functionally, in terms of goals, inputs, outputs, and relevant constraints; (b) procedurally, by means of workflow specifications; and (c) empirically, through a set of illustrative examples.

Clarence Cannon Re-regulation Structure, Salt River, Missouri : hydraulic model investigation /

"August 1996."

Modéle qui offre la restauration du Colisée de Rome tel qu'il était originairement : de la soixantième partie de la réalité mesure linéaire /

Mode of access: Internet.

A study and proposed re-design of the materials handling process for the Freeville Concrete Products Co., of Factory Street, Freeville, N. Y.

"Study made for Methods Engineering, Course 3262, Cornell University, for term paper, Fall, 1956."

Chemical dictionary, American and British usage. Containing the words generally used in chemistry, and many of the terms used in the related sciences of physics, astrophysics, mineralogy, pharmacy, agriculture, biology, medicine, engineering, etc.; based on recent chemical literature.

Re-issue, with changes and additions of the 3d ed. pub. in 1944.

Manuel de l'ingénieur des ponts et chaussées, rédigé conformément au programme annexé au Decret du 7 mars 1868 réglant l'admission des conducteurs des ponts et chaussées au grade d'ingénieur.

Text issued in 20 pts. Pt. 20, with title: Dictionnaire administratif des travaux publics is separately cataloged (HD4163.D3 1879)

Effect of cooling and re-warming on cerebral and whole body electrical impedance

Cerebral electrical impedance is useful for the detection of cerebral edema following hypoxia in newborn infants. Thus it may be useful for determining neurological outcome or monitoring treatment. Hypothermia is a promising new therapy currently undergoing trials, but will alter impedance measurements. This study aimed to define the relationship between temperature and both cerebral and whole body electrical impedance, and to derive correction factors for adjustment of impedance measurements during hypothermia. In eight anaesthetized 1-2 day old piglets rectal, tympanic and scalp temperatures were monitored continuously. Following baseline readings at a rectal temperature of 39degreesC, piglets were cooled to 32degreesC. Four piglets were re-warmed. Cerebral and whole body impedance were measured at each 0.5degreesC as rectal temperature decreased. There was a strong linear relationship between both cerebral and whole body impedance and each of the temperatures measured. There was no difference in the relationship between impedance and rectal, tympanic or scalp temperatures. The relationship for impedance and rectal temperature was the same during cooling and re-warming. Using the correction factors derived it will be possible to accurately monitor cerebral and whole body fluid distribution during hypothermic treatment.

Requirements-aware systems:a research agenda for RE for self-adaptive systems

Requirements are sensitive to the context in which the system-to-be must operate. Where such context is well-understood and is static or evolves slowly, existing RE techniques can be made to work well. Increasingly, however, development projects are being challenged to build systems to operate in contexts that are volatile over short periods in ways that are imperfectly understood. Such systems need to be able to adapt to new environmental contexts dynamically, but the contextual uncertainty that demands this self-adaptive ability makes it hard to formulate, validate and manage their requirements. Different contexts may demand different requirements trade-offs. Unanticipated contexts may even lead to entirely new requirements. To help counter this uncertainty, we argue that requirements for self-adaptive systems should be run-time entities that can be reasoned over in order to understand the extent to which they are being satisfied and to support adaptation decisions that can take advantage of the systems' self-adaptive machinery. We take our inspiration from the fact that explicit, abstract representations of software architectures used to be considered design-time-only entities but computational reflection showed that architectural concerns could be represented at run-time too, helping systems to dynamically reconfigure themselves according to changing context. We propose to use analogous mechanisms to achieve requirements reflection. In this paper we discuss the ideas that support requirements reflection as a means to articulate some of the outstanding research challenges.

How the web of things challenges requirements engineering

As a subset of the Internet of Things (IoT), the Web of Things (WoT) shares many characteristics with wireless sensor and actuator networks (WSANs) and ubiquitous computing systems (Ubicomp). Yet to a far greater degree than the IoT, WSANs or Ubicomp, the WoT will integrate physical and information objects, necessitating a means to model and reason about a range of context types that have hitherto received little or no attention from the RE community. RE practice is only now developing the means to support WSANs and Ubicomp system development, including faltering first steps in the representation of context. We argue that these techniques will need to be developed further, with a particular focus on rich context types, if RE is to support WoT application development. © 2012 Springer-Verlag.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Bayesian neural network approach for determining the risk of re-intervention after endovascular aortic aneurysm repair

This article proposes a Bayesian neural network approach to determine the risk of re-intervention after endovascular aortic aneurysm repair surgery. The target of proposed technique is to determine which patients have high chance to re-intervention (high-risk patients) and which are not (low-risk patients) after 5 years of the surgery. Two censored datasets relating to the clinical conditions of aortic aneurysms have been collected from two different vascular centers in the United Kingdom. A Bayesian network was first employed to solve the censoring issue in the datasets. Then, a back propagation neural network model was built using the uncensored data of the first center to predict re-intervention on the second center and classify the patients into high-risk and low-risk groups. Kaplan-Meier curves were plotted for each group of patients separately to show whether there is a significant difference between the two risk groups. Finally, the logrank test was applied to determine whether the neural network model was capable of predicting and distinguishing between the two risk groups. The results show that the Bayesian network used for uncensoring the data has improved the performance of the neural networks that were built for the two centers separately. More importantly, the neural network that was trained with uncensored data of the first center was able to predict and discriminate between groups of low risk and high risk of re-intervention after 5 years of endovascular aortic aneurysm surgery at center 2 (p = 0.0037 in the logrank test).

Recovery of glass fibre and carbon fibres from reinforced thermosets by batch pyrolysis and investigation of fibre re-using as reinforcement in LDPE matrix

A semi-batch pyrolysis process was used to recover samples carbon fibre and glass fibre from their respective wastes. The mechanical properties of the recovered fibres were tested and compared to those of virgin fibres, showing good retention of the fibre properties. The recovered fibres were then used to prepare new LDPE composite materials with commercial and laboratory-synthesized compatibilizers. Mild oxidation of the post-pyrolysis recovered fibres and the use of different compatibilizers gave significant improvements in the mechanical properties of the LDPE composites; however some of the manufactured composites made from recovered fibres had properties similar to those made from virgin fibres.

Naming the pain in requirements engineering: Contemporary problems, causes, and effects in practice

Requirements Engineering (RE) has received much attention in research and practice due to its importance to software project success. Its inter-disciplinary nature, the dependency to the customer, and its inherent uncertainty still render the discipline diffcult to investigate. This results in a lack of empirical data. These are necessary, however, to demonstrate which practically relevant RE problems exist and to what extent they matter. Motivated by this situation, we initiated the Naming the Pain in Requirements Engineering (NaPiRE) initiative which constitutes a globally distributed, bi-yearly replicated family of surveys on the status quo and problems in practical RE.

In this article, we report on the analysis of data obtained from 228 companies in 10 countries. We apply Grounded Theory to the data obtained from NaPiRE and reveal which contemporary problems practitioners encounter. To this end, we analyse 21 problems derived from the literature with respect to their relevance and criticality in dependency to their context, and we complement this picture with a cause-effect analysis showing the causes and effects surrounding the most critical problems.

Our results give us a better understanding of which problems exist and how they manifest themselves in practical environments. Thus, we provide a rst step to ground contributions to RE on empirical observations which, by now, were dominated by conventional wisdom only.