A Natural Language to Component Term Methodology: Towards a Form Based Concept Generation Tool

2009 ◽  
Author(s):  
Matt R. Bohm ◽  
Robert B. Stone
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Design Space ◽  
Design Method ◽  
Optimal Solution ◽  
Solution Space ◽  
Design Solution ◽  
Concept Generation ◽  
Language Interpretation ◽  
Interpretation Algorithm

Over the last few decades design researchers have put forward theories and proposed methodologies that increase the chance that a design team will reliably arrive at the optimal solution to a given design problem. Studies, however, bear out that theories and methodologies alone will not guarantee an optimal or even good design solution. Instead, a breadth of knowledge across multiple engineering domains and the time and tools to thoroughly evaluate the design space are as important as any prescriptive design method. This work presents one of the underlying engineering technologies needed to leverage artificial intelligence approaches to thoroughly search the design space and synthesize concept solutions. Artificial intelligence methods are employed to generate a natural language to formal component terms thesaurus as part of a novel form-initiated concept generation approach. With this fundamental natural language interpretation algorithm, designers may now suggest an initial solution to a problem, expressed in everyday terms, and then rely on a machine to abstract the underlying functionality and conduct a thorough search of the solution space.

Bridging Cross-Domain Terminology for Biomimetic Design

2005 ◽  
Author(s):  
I. Chiu ◽  
L. H. Shu
Keyword(s):  
Natural Language ◽  
Optimal Choice ◽  
Design Solution ◽  
Biological Knowledge ◽  
Concept Generation ◽  
Support Design ◽  
Domain Experts ◽  
Cross Domain ◽  
Biological Phenomena ◽  
Support Engineering

This work aims to improve creativity and innovation in design by facilitating the use of cross-domain analogies, particularly from biological phenomena, as stimulus for concept generation. Rather than create an enormous database of biological knowledge to specifically support engineering design, we have chosen to take advantage of the large amount of biological knowledge already in natural-language format, e.g., books, journals, etc. Relevant biological analogies for any given design problem are found by searching for instances of functional keywords that describe the intended effect of the design solution in a natural-language corpus. However, the optimal choice of keywords, or search terms, is complicated by the fact that engineers and biologists may use differing domain-specific lexicons to describe related concepts. Therefore, an engineer without sufficient background in biology may not be able to identify keywords with biological connotation that are not obviously related to the engineering keywords. This paper describes efforts to bridge the gap in lexicons by examining words that frequently collocate with searched words. The biological meaningfulness of these bridge words is characterized by how frequently they occur within definitions of biological terms in a biology dictionary. Search words identified this way may not be obvious to domain novices, and may parallel those suggested by domain experts, thus facilitating the use of cross-domain ideas to support design. Our approach of generating bridge words with biological meaningfulness is generic and can be used to bridge any disparate domains (e.g., engineering and economics). Thus designers are enabled to quickly access relevant concepts from different domains to produce more innovative solutions.

scholarly journals COMPUTATIONAL STUDY ON DESIGN SPACE EXPANSION DURING TEAMWORK

2021 ◽  
Vol 1 ◽  
pp. 691-700
Author(s):  
Marija Majda Perisic ◽  
Mario Štorga ◽  
John S. Gero
Keyword(s):  
Cognitive Processes ◽  
Design Space ◽  
Computational Study ◽  
Linear Trend ◽  
Solution Space ◽  
Cognitive Effort ◽  
Design Solution ◽  
Agent Based ◽  
Emerging Patterns ◽  
Space Expansion

AbstractWhen observing a design space expansion during teamwork, several studies found that cumulative solution-related issues' occurrence follows a linear trend. Such findings contradict the hypothesis of solution-related issues being characteristic for the later design stages. This work relies on agent-based simulations to explore the emerging patterns in design solution space expansion during teamwork. The results demonstrate trends that accord with the empirical findings, suggesting that a cognitive effort in solution space expansion remains constant throughout a design session. The collected data on agents' cognitive processes and solution space properties enabled additional insights, which led to the detection of four distinct regimes of design solution space expansion.

scholarly journals Prediction and Optimization of Production Quantities in Innoson Manufacturing Extraction Plastic Product

2019 ◽  
pp. 1-11
Author(s):  
Ezeliora, Chukwuemeka Daniel ◽  
Okoye, Peter Chukwuma ◽  
U. Mbabuike, Ikenna
Keyword(s):  
Factorial Design ◽  
Design Space ◽  
Design Method ◽  
Signal To Noise Ratio ◽  
Optimal Solution ◽  
Coefficient Of Determination ◽  
Anambra State ◽  
Plastic Pipes ◽  
Surface Plot ◽  
Production Quantity

In this research, it focused on the prediction and optimization of the production quantity in Innoson Plastic Manufacturing Company, Nnewi, Anambra State, Nigeria. The research method used is the application of factorial design methods to model, to evaluate the best optimal solutions for the production quantity of extrusion plastic pipes in the aforementioned company. The analysis shows that the parameters used to model the production quantity are significant and the model produced is also significant with its coefficient of determination to be 0.9968 and the adjusted R-Squared is 0.9823. Adequate Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 29.271 indicates an adequate signal. This model can be used to navigate the design space. The Model F-value of 68.99 implies the model is significant. There is only a 1.44% chance that an F-value this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. The 3D surface plot shows the effect of the variables in production system. It describes the variations of the input and output parameters in production of plastic extrusion products. The factorial design method applied shows the optimal solution which revealed that the best quantity of the product that is necessary to produce in any given month is 14414.112 units of a 25mm diameter plastic pipes with the optimal desirability of 100%. The tool also shows that the pigment is almost not important in the optimization of the product production quantity due to its insignificant quantity. However, the results further revealed that the industry should be conscious of highly influence input variable during production.

Design Method of Spring Balance Mechanism Through Derivation of General Solution

2019 ◽  
Vol 31 (2) ◽  
pp. 305-316 ◽  
Author(s):  
Kazuki Kaneda ◽  
Hirokazu Yamagata ◽  
Toshio Morita ◽  
◽  
Keyword(s):  
General Solution ◽  
Conventional Method ◽  
Design Method ◽  
Solution Space ◽  
Design Solution ◽  
Trial And Error ◽  
Mechanical Device ◽  
Spring Balance ◽  
Design Solutions ◽  
Balance Mechanism

The present study set out to devise a means of designing a spring-balance mechanism (hereinafter, a SBM) based on a general solution. The goal was to apply a general solution as a guideline for identifying the optimum design solution. A SBM is used to reduce the actuator output in the design of a mechanical device. As a result, the effect of gravity can be offset and energy-saving in operation can be realized. To date, however, SBMs have been designed on a trial and error basis, with a reliance on the designer’s knowledge or experience. Thus, in some instances, it may not be possible to identify a design solution that should, in theory, be achievable. To overcome this issue, this study examined the application of a general solution to the design of a SBM. Such a general solution would identify a solution space including viable design solutions. Subsequently, once a design that satisfies the general solution had been identified, a search could be made of all the design solutions within the solution space. First, the sequence whereby the general solution is used to identify a SBM design that satisfies the general solution, thus providing a guideline for the search action, is determined. Herein, the method used to identify this initial SBM design is presented. The devised method is based on the description of an energy-conservation formula that does not involve any trial and error. The proposed method incorporates a conventional method into the design solution, which can be derived when the conventional method cannot identify a design solution. As a result, a design method using a general solution for the design of an SBM is realized.

scholarly journals METHOD TO DEFINE MEASUREMENT UNCERTAINTY FOR DESIGN SPACE EXPLORATION IN ADDITIVE MANUFACTURING

2021 ◽  
Vol 1 ◽  
pp. 2067-2076
Author(s):  
Valentine Cazaubon ◽  
Audrey Abi Akle ◽  
Xavier Fischer
Keyword(s):  
Additive Manufacturing ◽  
Design Space Exploration ◽  
Design Space ◽  
Design Method ◽  
Optimal Solution ◽  
Feed Speed ◽  
Parameters Selection ◽  
Wire Feed Speed ◽  
Geometrical Defects ◽  
The Given

AbstractAdditive manufacturing is a process used for quick prototyping in industries. Geometrical defects are observed on printed parts. The aim of the paper is to propose a design method to implement measurements uncertainties into a Design Space for Additive Manufacturing parameters selection. To do so, two tests have been realized. The first test consists in determining the instrument’s uncertainty by measuring a standard length several times by an operator. The second test aim to determine the uncertainty within operators mesurement of geometric outputs (clad’s height, clad’s width, dilution’s height, dilution’s width and contact angle). Based on the results of our tests, uncertainties have been applied in our Design Space populated with 31 real printed clads. The uncertainties display with error bars on scatterplots allow to capitalize the knowledge for his/her exploration of the Design Space for future prints. The given information provides to ease the engineer to select the optimal solution (laser power, tool speed and wire feed speed) for his/her given Additive Manufacturing problematic among candidate points

Design Space Analysis Method for Support of System Design Under the Consideration of Uncertainties in the Early Design Stage

2020 ◽  
Author(s):  
Kazuhiro Aoyama ◽  
Yoshihiro Uchibori ◽  
Kazuya Oizumi ◽  
Shigeki Hiramatsu ◽  
Hiroshi Unesaki ◽  
...  
Keyword(s):  
System Design ◽  
Design Space ◽  
Solution Space ◽  
Design Stage ◽  
Design Solution ◽  
Analysis Method ◽  
Early Design Stage ◽  
Design Variables ◽  
Full Picture ◽  
Set Based Design

Abstract In this study, following the concept of set-based design, after preparing global calculation results, we introduced the approach of setting the design solution area that satisfies the product performance goals of the system design. In this approach, from the viewpoint of considering uncertainty, we aimed to develop an analysis method that can get the organic relationship between target variables and design variables. And more, under the assumption that it is difficult to comprehend the full picture of products that are becoming more sophisticated and complex with the knowledge that has been fostered by skilled engineers, the proposed system uses the objective calculation indices that is provided knowledge of the designer. Specifically, the following method are proposed to solve the problem. - Implementation of meta-modeling of design space. - Classified solution space using a density-based clustering method to detect that the solution spaces are divided into multiple disconnected space. - Defined an index called distribution concentration and expressed the possibility of dealing with the uncertainty of the solution domain. - The network diagram based on the calculated index values was proposed to confirm the change in the characteristics of the solution space when the performance target of the product was changed. Finally, the effectiveness of the proposed method was verified by applying it to actual simulation results.

Linguistic Data Model for Natural Languages and Artificial Intelligence. Part 5. Introduction to Logic

Discourse ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 109-117
Author(s):  
O. M. Polyakov
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Logic ◽  
Natural Language ◽  
Semantic Interpretation ◽  
General View ◽  
World Model ◽  
Semantic Approach ◽  
Natural Languages ◽  
The World ◽  
Linguistic Aspect

Introduction. The article continues the series of publications on the linguistics of relations (hereinafter R–linguistics) and is devoted to an introduction to the logic of natural language in relation to the approach considered in the series. The problem of natural language logic still remains relevant, since this logic differs significantly from traditional mathematical logic. Moreover, with the appearance of artificial intelligence systems, the importance of this problem only increases. The article analyzes logical problems that prevent the application of classical logic methods to natural languages. This is possible because R-linguistics forms the semantics of a language in the form of world model structures in which language sentences are interpreted.Methodology and sources. The results obtained in the previous parts of the series are used as research tools. To develop the necessary mathematical representations in the field of logic and semantics, the formulated concept of the interpretation operator is used.Results and discussion. The problems that arise when studying the logic of natural language in the framework of R–linguistics are analyzed. These issues are discussed in three aspects: the logical aspect itself; the linguistic aspect; the aspect of correlation with reality. A very General approach to language semantics is considered and semantic axioms of the language are formulated. The problems of the language and its logic related to the most General view of semantics are shown.Conclusion. It is shown that the application of mathematical logic, regardless of its type, to the study of natural language logic faces significant problems. This is a consequence of the inconsistency of existing approaches with the world model. But it is the coherence with the world model that allows us to build a new logical approach. Matching with the model means a semantic approach to logic. Even the most General view of semantics allows to formulate important results about the properties of languages that lack meaning. The simplest examples of semantic interpretation of traditional logic demonstrate its semantic problems (primarily related to negation).

A FORMALISM FOR REPRESENTING AND REASONING WITH LINGUISTIC INFORMATION

2002 ◽  
Vol 10 (03) ◽  
pp. 281-307 ◽  
Author(s):  
TRU H. CAO
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Natural Language ◽  
Functional Relation ◽  
Computing With Words ◽  
Conceptual Graphs ◽  
Graph Language ◽  
Conceptual Graph ◽  
Knowledge Representation Language ◽  
Representation Language

Conceptual graphs and fuzzy logic are two logical formalisms that emphasize the target of natural language, where conceptual graphs provide a structure of formulas close to that of natural language sentences while fuzzy logic provides a methodology for computing with words. This paper proposes fuzzy conceptual graphs as a knowledge representation language that combines the advantages of both the two formalisms for artificial intelligence approaching human expression and reasoning. Firstly, the conceptual graph language is extended with functional relation types for representing functional dependency, and conjunctive types for joining concepts and relations. Then fuzzy conceptual graphs are formulated as a generalization of conceptual graphs where fuzzy types and fuzzy attribute-values are used in place of crisp types and crisp attribute-values. Projection and join as basic operations for reasoning on fuzzy conceptual graphs are defined, taking into account the semantics of fuzzy set-based values.

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