scholarly journals Machine Learning for Fabrication of Graded Knitted Membranes

2021 ◽  
pp. 309-319
Author(s):  
Yuliya Sinke ◽  
Sebastian Gatz ◽  
Martin Tamke ◽  
Mette Ramsgaard Thomsen
Keyword(s):  
Machine Learning ◽  
Integrated Design ◽  
Computational Design ◽  
Parametric Models ◽  
Performance Criteria ◽  
Data Generation ◽  
Research Projects ◽  
Training Examples ◽  
Set Up

AbstractThis paper examines the use of machine learning in creating digitally integrated design-to-fabrication workflows. As computational design allows for new methods of material specification and fabrication, it enables direct functional grading of material at high detail thereby tuning the design performance in response to performance criteria. However, the generation of fabrication data is often cumbersome and relies on in-depth knowledge of the fabrication processes. Parametric models that set up for automatic detailing of incremental changes, unfortunately, do not accommodate the larger topological changes to the material set up. The paper presents the speculative case study KnitVault. Based on earlier research projects Isoropia and Ombre, the study examines the use of machine learning to train models for fabrication data generation in response to desired performance criteria. KnitVault demonstrates and validates methods for shortcutting parametric interfacing and explores how the trained model can be employed in design cases that exceed the topology of the training examples.

Organizing ODIN: a case study in European academic co-operation

1999 ◽  
Vol 14 (3) ◽  
pp. 177-181 ◽  
Author(s):  
C. Dowrick ◽  
J.L. Vázquez-Barquero ◽  
G. Wilkinson ◽  
C. Wilkinson ◽  
V. Lehtinen ◽  
...  
Keyword(s):  
European Commission ◽  
International Research ◽  
Communication Systems ◽  
Electronic Communication ◽  
Research Projects ◽  
International Network ◽  
Collaborative Groups ◽  
Principal Investigators ◽  
Set Up

SummaryThe European Commission is an increasingly important source of funding for international research projects and is due to announce its Framework 5 program early in 1999. The Outcomes of Depression International Network (ODIN), funded from the current EC Biomed 2 program, is a case study in European academic co-operation. Its organization has three key elements. First, engaging the principal investigators: this has involved identifying potential partners, ensuring reciprocity of interests, effective co-ordination, `dividing the spoils' in advance, and setting up good personal and electronic communication systems. Second, an esprit de corps has been created amongst the researchers, maintaining contact and consistency, and promoting higher degrees. Third, ongoing problems including difficulties in negotiations with the EC, divergence of detailed study methods, and isolation and demoralization amongst researchers, have been addressed. ODIN may provide a useful model for researchers wishing to set up international collaborative groups.

Use of novel 3D seismic technology and machine learning for pothole detection, characterization, and classification — Case study in the Bushveld Complex (South Africa)

2021 ◽  
Vol 40 (2) ◽  
pp. 106-113
Author(s):  
Steven E. Zhang ◽  
Lebogang Sehoole ◽  
Musa S. D. Manzi ◽  
Julie E. Bourdeau ◽  
Glen T. Nwaila
Keyword(s):  
Machine Learning ◽  
Bushveld Complex ◽  
Empirical Relationship ◽  
Mining Industry ◽  
Data Generation ◽  
Agglomerative Clustering ◽  
Reflection Seismics ◽  
Characteristic Features ◽  
Classification Prediction

We demonstrate that integrating 3D reflection seismics with machine learning (ML) can bring many benefits for the future development of the mining industry. We use a serial integration of reflection seismics, which identifies economic horizon-depression structures known as potholes within the western Bushveld Complex. Thereafter, agglomerative clustering is applied to the resulting data, using features engineered from the physical characteristics of the potholes. Our results indicate that potholes can be divided into several classes based on characteristic features; e.g., large potholes are substantially less steep than small potholes. Furthermore, we model this empirical relationship and show that it can be used to predict average sizes of potholes given their typical in-mine exposures. We also demonstrate that pothole formation is likely to have been initiated depth-wise, followed by lateral increases in size. Lastly, we demonstrate that our serial application of seismically based data generation and ML-based data analytics is a viable alternative to conventional geostastistical analysis, especially for the classification, prediction, and modeling of geologic structures such as potholes.

Paper2Wire – A Case Study of User-Centred Development of Machine Learning Tools for UX Designers

i-com ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 19-32
Author(s):  
Daniel Buschek ◽  
Charlotte Anlauff ◽  
Florian Lachner
Keyword(s):  
Machine Learning ◽  
Development Process ◽  
User Study ◽  
Concept Development ◽  
Lessons Learned ◽  
Design Tool ◽  
Learning Tools ◽  
Interface Elements ◽  
Industry Partner

Abstract This paper reflects on a case study of a user-centred concept development process for a Machine Learning (ML) based design tool, conducted at an industry partner. The resulting concept uses ML to match graphical user interface elements in sketches on paper to their digital counterparts to create consistent wireframes. A user study (N=20) with a working prototype shows that this concept is preferred by designers, compared to the previous manual procedure. Reflecting on our process and findings we discuss lessons learned for developing ML tools that respect practitioners’ needs and practices.

scholarly journals APPLICATION OF DOMAIN INTEGRATED DESIGN METHODOLOGY FOR BIO-INSPIRED DESIGN- A CASE STUDY OF SUTURE PIN DESIGN

2021 ◽  
Vol 1 ◽  
pp. 487-496
Author(s):  
Pavan Tejaswi Velivela ◽  
Nikita Letov ◽  
Yuan Liu ◽  
Yaoyao Fiona Zhao
Keyword(s):  
Cross Sections ◽  
Design Methodology ◽  
Reaction Force ◽  
Integrated Design ◽  
Total Deformation ◽  
Insertion Force ◽  
Force Reaction ◽  
The Moment ◽  
Work Done

AbstractThis paper investigates the design and development of bio-inspired suture pins that would reduce the insertion force and thereby reducing the pain in the patients. Inspired by kingfisher's beak and porcupine quills, the conceptual design of the suture pin is developed by using a unique ideation methodology that is proposed in this research. The methodology is named as Domain Integrated Design, which involves in classifying bio-inspired structures into various domains. There is little work done on such bio-inspired multifunctional aspect. In this research we have categorized the vast biological functionalities into domains namely, cellular structures, shapes, cross-sections, and surfaces. Multi-functional bio-inspired structures are designed by combining different domains. In this research, the hypothesis is verified by simulating the total deformation of tissue and the needle at the moment of puncture. The results show that the bio-inspired suture pin has a low deformation on the tissue at higher velocities at the puncture point and low deformation in its own structure when an axial force (reaction force) is applied to its tip. This makes the design stiff and thus require less force of insertion.

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