Investigating novelty-outcome relationships in engineering design

Design creativity involves developing novel and useful solutions to design problems The research in this article is an attempt to understand how novelty of a design resulting from a design process is related to the kind of outcomes. described here as constructs, involved in the design process A model of causality, the SAPPhIRE model, is used as the basis of the analysis The analysis is based on previous research that shows that designing involves development and exploration of the seven basic constructs of the SAPPhIRE model that constitute the causal connection between the various levels of abstraction at which a design can be described The constructs am state change, action, parts. phenomenon. input. organs. and effect The following two questions are asked. Is there a relationship between novelty and the constructs? If them is a relationship, what is the degree of this relationship? A hypothesis is developed to answer the questions an increase in the number and variety of ideas explored while designing should enhance the variety of concept space. leading to an increase in the novelty of the concept space Eight existing observational studies of designing sessions are used to empirically validate the hypothesis Each designing session involves an individual designer. experienced or novice. solving a design problem by producing concepts and following a think-aloud protocol. The results indicate dependence of novelty of concept space on variety of concept space and dependence of variety of concept space on variety of idea space. thereby validating the hypothesis The Jesuits also reveal a strong correlation between novelty and the constructs, correlation value decreases as the abstraction level of the constructs reduces. signifying the importance of using constructs at higher abstraction levels for enhancing novelty

An Empirical Evaluation of Novelty-SAPPhIRE Relationship

The research shown in this paper is to check whether a framework for designing: GEMS of SAPPhIRE as req-sol, developed earlier, can support in the designing of novel concepts. This is done by asking the questions: (a) Is there a relationship between the constructs of the framework and novelty? (b) If there is a relationship, what is the degree of this relationship? A hypothesis — an increase in the size and variety of ideas used while designing should enhance the variety of concepts produced, leading to an increase in the novelty of the concept space — is developed to explain the relationship between novelty and the constructs. Eight existing observational studies of designing sessions, each involving an individual designer solving a conceptual design problem by following a think aloud protocol are used for the analysis. The hypothesis is verified empirically using the observational studies. Results also show a strong correlation between novelty and the constructs of the framework; correlation value decreases as the abstraction level of the constructs reduces, signifying the importance of using constructs at higher abstraction levels especially for novelty.

Assessing Degree of Novelty of Products to Ascertain Innovative Products

Substantial increase in competition compels design firms to develop new products at an increasingly rapid pace. This situation pressurizes engineering teams to develop better products and at the same time develop products faster [1]. Continuous innovation is a key factor to enable a company to generate profit on a continued basis, through the introduction of new products in the market – a prime intention for Product Lifecycle Management. Creativity, affecting a wide spectrum of business portfolios, is regarded as the crucial factor for designing products. A central goal of product development is to create products that are sufficiently novel and useful. This research focuses on the determination of novelty of engineering products. Determination of novelty is important for ascertaining the newness of a product, to decide on the patentability of the design, to compare designers' capability of solving problems and to ascertain the potential market of a product. Few attempts at measuring novelty is available in literature [2, 3, 4], but more in-depth research is required for assessing degree of novelty of products. This research aims to determine the novelty of a product by enabling a person to determine the degree of novelty in a product. A measure of novelty has been developed by which the degree of ''novelty'' of products can be ascertained. An empirical study has been conducted to determine the validity of this method for determining the 'novelty' of the products.

An empirical evaluation of a framework for design for variety and novelty

The objective of this paper is to empirically evaluate a framework for designing – GEMS of SAPPhIRE as req-sol – to check if it supports design for variety and novelty. A set of observational studies is designed where three teams of two designers each, solve three different design problems in the following order: without any support, using the framework, and using a combination of the framework and a catalogue. Results from the studies reveal that both variety and novelty of the concept space increases with the use of the framework or the framework and the catalogue. However, the number of concepts and the time taken by the designers decreases with the use of the framework and, the framework and the catalogue. Based on the results and the interview sessions with the designers, an interactive framework for designing to be supported on a computer is proposed as future work.

Robust and High-resolution Voiced/Unvoiced Classification in Noisy Speech Using A Signal Smoothness Criterion

We propose a novel technique for robust voiced/unvoiced segment detection in noisy speech, based on local polynomial regression. The local polynomial model is well-suited for voiced segments in speech. The unvoiced segments are noise-like and do not exhibit any smooth structure. This property of smoothness is used for devising a new metric called the variance ratio metric, which, after thresholding, indicates the voiced/unvoiced boundaries with 75% accuracy for 0dB global signal-to-noise ratio (SNR). A novelty of our algorithm is that it processes the signal continuously, sample-by-sample rather than frame-by-frame. Simulation results on TIMIT speech database (downsampled to 8kHz) for various SNRs are presented to illustrate the performance of the new algorithm. Results indicate that the algorithm is robust even in high noise levels.

Soft matter lithium salt electrolytes: ion conduction and application to rechargeable batteries

Soft matter provides diverse opportunities for the development of electrolytes for all solid state lithium batteries. Here we review soft matter solid electrolytes for lithium batteriesthat are primarily obtained starting from liquid electrolytic systems. This concept of solid electrolyte synthesis from liquid is significantly different from prevalent approaches. The novelty of our approach is discussed in the light of various fundamental issues and in relation to its application to rechargeable lithium batteries.

Modeling and analysis of a tunable piezoelectric structure for transverse shear wave generation

An analytical investigation of the transverse shear wave mode tuning with a resonator mass (packing mass) on a Lead Zirconium Titanate (PZT) crystal bonded together with a host plate and its equivalent electric circuit parameters are presented. The energy transfer into the structure for this type of wave modes are much higher in this new design. The novelty of the approach here is the tuning of a single wave mode in the thickness direction using a resonator mass. First, a one-dimensional constitutive model assuming the strain induced only in the thickness direction is considered. As the input voltage is applied to the PZT crystal in the thickness direction, the transverse normal stress distribution induced into the plate is assumed to have parabolic distribution, which is presumed as a function of the geometries of the PZT crystal, packing mass, substrate and the wave penetration depth of the generated wave. For the PZT crystal, the harmonic wave guide solution is assumed for the mechanical displacement and electric fields, while for the packing mass, the former is solved using the boundary conditions. The electromechanical characteristics in terms of the stress transfer, mechanical impedance, electrical displacement, velocity and electric field are analyzed. The analytical solutions for the aforementioned entities are presented on the basis of varying the thickness of the PZT crystal and the packing mass. The results show that for a 25% increase in the thickness of the PZT crystal, there is ~38% decrease in the first resonant frequency, while for the same change in the thickness of the packing mass, the decrease in the resonant frequency is observed as ~35%. Most importantly the tuning of the generated wave can be accomplished with the packing mass at lower frequencies easily. To the end, an equivalent electric circuit, for tuning the transverse shear wave mode is analyzed.

Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains

We consider the problem of detecting statistically significant sequential patterns in multineuronal spike trains. These patterns are characterized by ordered sequences of spikes from different neurons with specific delays between spikes. We have previously proposed a data-mining scheme to efficiently discover such patterns, which occur often enough in the data. Here we propose a method to determine the statistical significance of such repeating patterns. The novelty of our approach is that we use a compound null hypothesis that not only includes models of independent neurons but also models where neurons have weak dependencies. The strength of interaction among the neurons is represented in terms of certain pair-wise conditional probabilities. We specify our null hypothesis by putting an upper bound on all such conditional probabilities. We construct a probabilistic model that captures the counting process and use this to derive a test of significance for rejecting such a compound null hypothesis. The structure of our null hypothesis also allows us to rank-order different significant patterns. We illustrate the effectiveness of our approach using spike trains generated with a simulator.

Robust fixed order lateral H-2 controller for micro air vehicle

This paper presents a robust fixed order H-2 controller design using Strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H-2 controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation.

An Integrated Model of Designing

Current design models and frameworks describe various overlapping fragments of designing. However, little effort exists in consolidating these fragments into an integrated model. We propose a model of designing that integrates product and process facets of designing by combining activities, outcomes, requirements, and solutions. Validation of the model using video protocols of design sessions demonstrates that all the constructs are used naturally by designers but often not to the expected level, which hinders the variety and resulting novelty of the concepts developed in these sessions. To resolve this, a prescriptive framework for supporting design for variety and novelty is proposed and plans for its implementation are created. DOI: 10.1115/1.3467011]

Chance constrained uncertain classification via robust optimization

This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out to be intractable. The key novelty is in employing Bernstein bounding schemes to relax the CCP as a convex second order cone program whose solution is guaranteed to satisfy the probabilistic constraint. Prior to this work, only the Chebyshev based relaxations were exploited in learning algorithms. Bernstein bounds employ richer partial information and hence can be far less conservative than Chebyshev bounds. Due to this efficient modeling of uncertainty, the resulting classifiers achieve higher classification margins and hence better generalization. Methodologies for classifying uncertain test data points and error measures for evaluating classifiers robust to uncertain data are discussed. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle data uncertainty and outperform state-of-the-art in many cases.