Categorizing biological information based on function–morphology for bioinspired conceptual design

2016 ◽  
Vol 31 (3) ◽  
pp. 359-375
Author(s):  
Sooyeon Lee ◽  
Daniel A. McAdams ◽  
Elissa Morris
Keyword(s):  
Penalty Function ◽  
Semantic Analysis ◽  
Keyword Search ◽  
Expectation Maximization Algorithm ◽  
Biological Information ◽  
Algorithm Engineering ◽  
Concept Generation ◽  
Search Methods ◽  
Efficient Manner ◽  
Biological Inspiration

AbstractA function-based keyword search is a concept generation methodology studied in the bioinspired design area that conveys textual biological inspiration for engineering design. Current keyword search methods are inefficient primarily due to the knowledge gap between engineering and biology domains. To improve current keyword search methods, we propose an algorithm that extracts and organizes morphology-based solutions from biological text. WordNet is utilized to discover morphological solutions in biological text. The novel algorithm also adapts latent semantic analysis and the expectation–maximization algorithm to categorize morphological solutions and group biological text. We introduce a novel penalty function that reflects the distance between functions (problems) and morphologies (solutions). The penalty function allows the algorithm to extract morphological solutions directly related to a design problem. We compare the output of the algorithm to manually extracted solutions for validation. A case study is included to exemplify the utility of the developed algorithm. Upon implementation of the algorithm, engineering designers can discover innovative solutions in biological text in a straightforward, efficient manner.

Fostering Diverse Analogical Transfer in Bio-Inspired Design

2015 ◽  
Author(s):  
Jacquelyn K. S. Nagel ◽  
Linda Schmidt ◽  
Werner Born
Keyword(s):  
Knowledge Transfer ◽  
Best Practices ◽  
Biological System ◽  
Engineering Students ◽  
Natural World ◽  
Physical Characteristics ◽  
Biological Information ◽  
Concept Generation ◽  
Analogical Transfer ◽  
Design Inspiration

Nature is a powerful resource for engineering designers. The natural world provides numerous cases for analogy and inspiration in engineering design. Transferring the valuable knowledge and inspiration gained from the biology domain to the engineering domain during concept generation is a somewhat disorganized process and relies heavily on the designers’ insight and background knowledge of many fields to make the necessary leaps between the domains. Furthermore, the novice designer approaching biology for inspiration tends to focus heavily on copying the visual attributes of a biological system to develop a solution that looks like the biological system rather than explore at deeper levels to uncover relationships that lead to the development of true analogies. There are now well-known methods for teaching bioinspired design in engineering and the majority of methods prescribe the use of analogies in order to facilitate knowledge transfer, however, guidance in analogy formulation to foster the creative leaps is missing or ill defined. Thus little is known about how students use biological systems for design inspiration. This paper proposes categories for analogical knowledge transfer in bio-inspired design to foster and characterize diverse analogical knowledge transfer. The proposed analogy categories are used to describe the behavior seen in an engineering class. Results indicate that (1) single biological system provides multiple analogies that result in different engineering inspiration for design; (2) biological information from multiple categories is transferred during concept generation; and (3) non-physical characteristics may inspire more sophisticated engineering inspiration than those based on physical characteristics alone. Overall, the analogy data classification has resulted in a better understanding of analogical knowledge transfer during bio-inspired design and leads to best practices for teaching bio-inspired design to engineering students.

Supporting Biomimetic Design Through Categorization of Natural-Language Keyword-Search Results

2009 ◽  
Author(s):  
Ji Ke ◽  
J. S. Wallace ◽  
L. H. Shu
Keyword(s):  
Fuel Cell ◽  
Natural Language ◽  
Keyword Search ◽  
Bipolar Plate ◽  
Biological Information ◽  
Good Source ◽  
Search Results ◽  
Biological Phenomena ◽  
Keyword Searches

Biology is a good source of analogies for engineering design. One approach of retrieving biological analogies is to perform keyword searches on natural-language sources such as books, journals, etc. A challenge of retrieving information from natural-language sources is the potential requirement to process a large number of search results. This paper describes a categorization method that organizes a large group of diverse biological information into meaningful categories. The benefits of the categorization functionality are demonstrated through a case study on the redesign of a fuel cell bipolar plate. In this case study, our categorization method reduced the effort to systematically identify biological phenomena by up to ∼80%.

Function-based, biologically inspired concept generation

2010 ◽  
Vol 24 (4) ◽  
pp. 521-535 ◽  
Author(s):  
Jacquelyn K.S. Nagel ◽  
Robert L. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Engineering Design ◽  
Biological Systems ◽  
Natural World ◽  
Biological Information ◽  
Biological Knowledge ◽  
Concept Generation ◽  
Biologically Inspired ◽  
Modeling Methodology ◽  
Functional Representation ◽  
Engineering Designs

AbstractThe natural world provides numerous cases for inspiration in engineering design. Biological organisms, phenomena, and strategies, which we refer to as biological systems, provide a rich set of analogies. These systems provide insight into sustainable and adaptable design and offer engineers billions of years of valuable experience, which can be used to inspire engineering innovation. This research presents a general method for functionally representing biological systems through systematic design techniques, leading to the conceptualization of biologically inspired engineering designs. Functional representation and abstraction techniques are used to translate biological systems into an engineering context. The goal is to make the biological information accessible to engineering designers who possess varying levels of biological knowledge but have a common understanding of engineering design. Creative or novel engineering designs may then be discovered through connections made between biology and engineering. To assist with making connections between the two domains concept generation techniques that use biological information, engineering knowledge, and automatic concept generation software are employed. Two concept generation approaches are presented that use a biological model to discover corresponding engineering components that mimic the biological system and use a repository of engineering and biological information to discover which biological components inspire functional solutions to fulfill engineering requirements. Discussion includes general guidelines for modeling biological systems at varying levels of fidelity, advantages, limitations, and applications of this research. The modeling methodology and the first approach for concept generation are illustrated by a continuous example of lichen.

scholarly journals Grand challenges and entrepreneurship: Emerging issues, research streams, and theoretical landscape

2021 ◽  
Author(s):  
Francesca Ricciardi ◽  
Cecilia Rossignoli ◽  
Alessandro Zardini
Keyword(s):  
Semantic Analysis ◽  
Keyword Search ◽  
Complex Dynamics ◽  
Grand Challenges ◽  
Emerging Issues ◽  
The Commons ◽  
Development Goals ◽  
Research Stream ◽  
Selection Of

AbstractThis study discusses how the role of entrepreneurship in addressing the so-called “grand challenges” (e.g., poverty, inequality, pollution, climate change) is evolving and could further evolve, based on the ongoing conversation in the scholarly community. To develop the discussion, we conducted the following steps: (1) a computer-aided semantic analysis; (2) an analysis of the evolution of literature streams; and (3) a network analysis of advocated theories and approaches. All three analyses were based on a selection of 358 publications retrieved via a keyword search and 27 further publications retrieved via an analysis of five recent and relevant special issues published by important scientific journals. Our results show that the call to address grand challenges, particularly after the publication of the United Nations’ Sustainable Development Goals (SDGs), is radically transforming entrepreneurship research, with new issues emerging and replacing traditional issues as core to the discipline, marking a rapid and complex dynamics of research stream divergence and convergence. Similarly, the network of theories and approaches advocated by recent agenda-setting articles depicts an emerging theoretical landscape that is highly innovative. This new theoretical landscape revolves around systems thinking and Ostrom’s theory of the commons as the two key poles, with the embeddedness, stakeholder, institutional, effectuation, processual, and design-oriented approaches being the cross-fertilizing forces linking these two poles. In the final section, we present the nine articles included in the special issue titled “Grand Challenges and Entrepreneurship: Emerging Issues and Research Streams” and briefly synthesize these in the light of the ongoing evolution of the literature.

Can many agents answer questions better than one?

First Monday ◽  
2005 ◽  
Author(s):  
Boris Galitsky ◽  
Rajesh Pampapathi
Keyword(s):  
Question Answering ◽  
Semantic Analysis ◽  
Keyword Search ◽  
Commercial Application ◽  
Specific Knowledge ◽  
Domain Experts ◽  
Retrieval Systems ◽  
Natural Language Question ◽  
Information Retrieval Systems ◽  
Better Than

The paper addresses the issue of how online natural language question answering, based on deep semantic analysis, may compete with currently popular keyword search, open domain information retrieval systems, covering a horizontal domain. We suggest the multiagent question answering approach, where each domain is represented by an agent which tries to answer questions taking into account its specific knowledge. The meta–agent controls the cooperation between question answering agents and chooses the most relevant answer(s). We argue that multiagent question answering is optimal in terms of access to business and financial knowledge, flexibility in query phrasing, and efficiency and usability of advice. The knowledge and advice encoded in the system are initially prepared by domain experts. We analyze the commercial application of multiagent question answering and the robustness of the meta–agent. The paper suggests that a multiagent architecture is optimal when a real world question answering domain combines a number of vertical ones to form a horizontal domain.

An Engineering-to-Biology Thesaurus for Engineering Design

2010 ◽  
Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Idea Generation ◽  
Natural World ◽  
Biological Information ◽  
Concept Generation ◽  
Functional Modeling ◽  
University Of Toronto ◽  
Engineering Designs ◽  
Design Activities

Engineering design is considered a creative field that involves many activities with the end goal of a new product that fulfills a purpose. Utilization of systematic methods or tools that aid in the design process is recognized as standard practice in industry and academia. The tools are used for a number of design activities (i.e., idea generation, concept generation, inspiration searches, functional modeling) and can span across engineering disciplines, the sciences (i.e., biology, chemistry) or a non-engineering domain (i.e., medicine), with an overall focus of encouraging creative engineering designs. Engineers, however, have struggled with utilizing the vast amount of biological information available from the natural world around them. Often it is because there is a knowledge gap or terminology is difficult, and the time needed to learn and understand the biology is not feasible. This paper presents an engineering-to-biology thesaurus, which we propose affords engineers, with limited biological background, a tool for leveraging nature’s ingenuity during many steps of the design process. Additionally, the tool could also increase the probability of designing biologically-inspired engineering solutions. Biological terms in the thesaurus are correlated to the engineering domain through pairing with a synonymous function or flow term of the Functional Basis lexicon, which supports functional modeling and abstract representation of any functioning system. The second version of the thesaurus presented in this paper represents an integration of three independent research efforts, which include research from Oregon State University, the University of Toronto, and the Indian Institute of Science, and their industrial partners. The overall approach for term integration and the final results are presented. Applications to the areas of design inspiration, comprehension of biological information, functional modeling, creative design and concept generation are discussed. An example of comprehension and functional modeling are presented.

scholarly journals YouTube Keyword Search Engine Using Speech Recognition

2021 ◽  
pp. 167-173
Author(s):  
Aymen Shakat ◽  
Khaldun Ibraheem Arif ◽  
Sami Hasan ◽  
Yaser Dawood ◽  
Mohammed A. Mohammed
Keyword(s):  
Speech Recognition ◽  
Search Engine ◽  
Keyword Search ◽  
Visual Media ◽  
Search Methods ◽  
Java Language

Visual media is a better way to deliver the information than the old way of "reading". For that reason with the wide propagation of multimedia websites, there are large video library’s archives, which came to be a main resource for humans. This research puts its eyes on the existing development in applying classical phrase search methods to a linked vocal transcript and after that it retrieves the video, this an easier way to search any visual media. This system has been implemented using JSP and Java language for searching the speech in the videos

A computational approach to biologically inspired design

2012 ◽  
Vol 26 (2) ◽  
pp. 161-176 ◽  
Author(s):  
Jacquelyn K.S. Nagel ◽  
Robert B. Stone
Keyword(s):  
Computational Design ◽  
Natural World ◽  
Computational Approach ◽  
Concept Generation ◽  
Biologically Inspired ◽  
Biological Inspiration ◽  
Early Stages ◽  
Innovative Solutions ◽  
Biological Domain ◽  
Biologically Inspired Design

AbstractThe natural world provides numerous cases for analogy and inspiration in engineering design. During the early stages of design, particularly during concept generation when several variants are created, biological systems can be used to inspire innovative solutions to a design problem. However, identifying and presenting the valuable knowledge from the biological domain to an engineering designer during concept generation is currently a somewhat disorganized process or requires extensive knowledge of the biological system. To circumvent the knowledge requirement problem, we developed a computational approach for discovering biological inspiration during the early stages of design that integrates with established function-based design methods. This research defines and formalizes the information identification and knowledge transfer processes that enable systematic development of biologically inspired designs. The framework that supports our computational design approach is provided along with an example of a smart flooring device to demonstrate the approach. Biologically inspired conceptual designs are presented and validated through a literature search and comparison to existing products.

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