Mapping the Design Criterion Framework for Museum Exhibition Design Project

Currently, museums are struggling to develop and present their expertise by focusing on the interactive relationship with museum visitors. In order to meet the needs of museum exhibitions, an efficient and workable design process is of primary importance in order to work to develop high quality museum exhibitions. It would be advantageous to generate a design method which allows designers and curators to undertake design work in the context of museum exhibition project. Based on an empirical analysis, this paper suggests that a systematic transformation develops specific aspects of detailed design to carry out its principle, and that the implementation of these aspects can be viewed as a process of organizational criteria of museum exhibition design projects. The paper is concerned with design process in organizations seeking to act systematic criteria in the design activity on the application of museum exhibition project development in complex theories. In particular, this study is developed to address the following objectives: a) To identify the characteristics and concepts of the design activity as they relate to museum exhibition design; b) To contribute to a more complete understanding of design process by developing guidelines for adoption in projects. c) To establish the benefits of the application of design guide theory to the practice of museum exhibition design; Keywords: Museum Exhibition; Design Criteria; Design Process</p

Generalized Methodology for Array Processor Design of Real-time Systems

Many techniques and design tools have been developed for mapping algorithms to array processors. Linear mapping is usually used for regular algorithms. Large and complex problems are not regular by nature and regularization may cause a computational overhead which prevents the ability to meet real-time deadlines. In this paper, a systematic design methodology for mapping partially-regular as well as regular Dependence Graphs is presented. In this approach the set of all optimal solutions is generated under the given constraints. Due to nature of the problem and the tight timing constraints of real-time systems the set of alternative solutions is limited. An image processing example is discusse

Design of Dispersive Delay Structures (DDSs) Formed by Coupled C-Sections Using Predistortion with Space Mapping

The concept of space mapping is applied, for the first time, to the design of microwave dispersive delay structures (DDSs). DDSs are components providing specified group delay versus frequency responses for real-time radio systems. The DDSs considered in this paper are formed by cascaded coupled C-sections. It is first shown that aggressive space mapping does not provide sufficient accuracy in the synthesis of DDSs. To address this issue, we propose a predistortion space mapping technique. Compared to aggressive space mapping, this technique provides enhanced accuracy, while compared to output space mapping, it provides greater implementation simplicity. Two full-wave and one experimental examples are provided to illustrate the proposed predistortion space mapping technique

Introduction to fMRI: experimental design and data analysis

This provides an introduction to functional MRI, experimental design and data analysis procedures using statistical parametric mapping approach

Musical instrument mapping design with Echo State Networks

Echo State Networks (ESNs), a form of recurrent neural network developed in the field of Reservoir Computing, show significant potential for use as a tool in the design of mappings for digital musical instruments. They have, however, seldom been used in this area, so this paper explores their possible applications. This project contributes a new open source library, which was developed to allow ESNs to run in the Pure Data dataflow environment. Several use cases were explored, focusing on addressing current issues in mapping research. ESNs were found to work successfully in scenarios of pattern classification, multiparametric control, explorative mapping and the design of nonlinearities and uncontrol. 'Un-trained' behaviours are proposed, as augmentations to the conventional reservoir system that allow the player to introduce potentially interesting non-linearities and uncontrol into the reservoir. Interactive evolution style controls are proposed as strategies to help design these behaviours, which are otherwise dependent on arbitrary values and coarse global controls. A study on sound classification showed that ESNs could reliably differentiate between two drum sounds, and also generalise to other similar input. Following evaluation of the use cases, heuristics are proposed to aid the use of ESNs in computer music scenarios

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved