Scalability of the Approach

The criteria for evaluation of matching tools needs to be specified. This should include usability features, technical details about what ontologies are supported, as well as criteria for evaluating the scalability of the approach. 

Abstract. Artificial neural networks (ANN) are useful components in today s data analysis toolbox. They were initially inspired by the brain but are today accepted to be quite different from it. ANN typically lack scalability and mostly rely on supervised learning, both of which are biologically implausible features. Here we describe and evaluate a novel cortex-inspired hybrid algorithm. It is found to perform on par with a Support Vector Machine (SVM) in classification of activation patterns from the rat olfactory bulb. On-line unsupervised learning is shown to provide significant tolerance to sensor drift, an important property of algorithms used to analyze chemo-sensor data. Scalability of the approach is illustrated on the MNIST dataset of handwritten digits. 

Further work would include the enhancement of singular components to work with higher granularity. Most efforts would have to be undertaken to improve DRM/ERM. Further standardization of IPP-related interfaces is also necessary. Finally, validation of the scalability of the approaches for large assembly sets as well as visualization of large relationship graphs remain as further objectives. 

The QShAR (Quantitative Shape-Activity Relations) method, combined with the integrated main and side effect modeling of bioactive molecules, forms the conceptual basis of the approaches described in this chapter. The density scalable FSGH method for a simple representation of molecular bodies, in combination with the Shape Group Method and various other shape code approaches for quantitative shape analysis, as well as the multiple shape ranking methods for integrated main and side effect analysis, are the components of a computational implementation of the basic concepts. 

Although online monitoring was an improvement from the off-line assay, internal capabilities, both hardware and experience, for implementation in the pilot plant did not exist. In addition, the scalability of the technique with regard to cool-down time cycles and overreaction during the cool down was a concern. As a result, the reaction engineering approach was developed as the primary solution to overreaction of the vinyl ether, providing a robust and immediate solution. To address the issue of internal mid-IR capabilities, the implementation of online monitoring of this reaction was also pursued. 

In the near future we plan to automate the tradeoff analysis of the security configurations by automatically exploring the trade space. Such automation is feasible because performance models embedding security properties are generated once and the exploration of the trade space can be automatically performed by instrumenting the model with different numerical values for the input parameters. Besides, we devise to apply our approach to other real world examples in order to assess the scalability of the framework. 

This RQ aims at adaptation of ER approach to a goal structured safety case. We need to identify ways in which the confidence can be quantified in the argument patterns proposed [5]. We also need to identify ways in which the assurance deficit is captured and communicated to the assessor. As a potential challenge, we need to account for the fact that the confidence arguments are not necessarily tree-structured. We need to identify an approach that enables feeding the answers to the questions (see RQl) into the ER framework and efficiently propagate these lower-level belief values to the top-level claims. Implementation of the approach with a scalable tool support is also a major step in this RQ. 

In multiple domains the embedded systems architecture follows a federated approach, in which the system is composed of multiple interconnected subsystems where each of them provides a well defined functionality. The ever increasing demand for additional functionalities leads to an increase in the number of subsystems, connectors and wires leading to an increase in the the overall cost-size-weight-power and complexity [25] that in some cases limits the scalability of this approach. For example [32,33] ... 

The number of integrated functionalities will continue to increase and the future scalability of this approach is limited as previously described, e.g., limited by the computation power of single core processor(s) and reliability restrictions (e.g., usage of fans is not allowed). If processor PI does not provide sufficient computation power new processors / nodes will be needed. Adding new processors / nodes and their associated communication buses leads to additional reliability and availability issues (e.g., material reliability, EMC). 

Abstract This study presents an Augmented Reality Interface for engineering education. The interface, designed to use Augmented Reality to facilitate learning, is composed of both specific software and hardware elements and provides useful information and assistance in Electronic Laboratories. The document first presents the overall system and its objectives under the E2LP project. Then its components, their functioning and adaptation to educational purposes are discussed in detail. The study concludes with the approach of the scalability of the system and its future use in classrooms. 

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