scholarly journals intern: Integrated Toolkit for Extensible and Reproducible Neuroscience

2020 ◽  
Author(s):  
Jordan Matelsky ◽  
Luis Rodriguez ◽  
Daniel Xenes ◽  
Timothy Gion ◽  
Robert Hider ◽  
...  
Keyword(s):  
Computer Science ◽  
Design Patterns ◽  
Use Cases ◽  
Heterogeneous Environment ◽  
Data Standards ◽  
Detailed Understanding ◽  
Data Analyses ◽  
General Data ◽  
Reference Implementation ◽  
Research Investments

AbstractAs neuroscience datasets continue to grow in size, the complexity of data analyses can require a detailed understanding and implementation of systems computer science for storage, access, processing, and sharing. Currently, several general data standards (e.g., Zarr, HDF5, precompute, tensorstore) and purpose-built ecosystems (e.g., BossDB, CloudVolume, DVID, and Knossos) exist. Each of these systems has advantages and limitations and is most appropriate for different use cases. Using datasets that don’t fit into RAM in this heterogeneous environment is challenging, and significant barriers exist to leverage underlying research investments. In this manuscript, we outline our perspective for how to approach this challenge through the use of community provided, standardized interfaces that unify various computational backends and abstract computer science challenges from the scientist. We introduce desirable design patterns and our reference implementation called intern.

scholarly journals A Pattern Approach to Comprehensible and Pleasant Human–Robot Interaction

2021 ◽  
Vol 5 (9) ◽  
pp. 49
Author(s):  
Kathrin Pollmann ◽  
Daniel Ziegler
Keyword(s):  
Design Patterns ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Use Cases ◽  
Pattern Language ◽  
Robot Design ◽  
Behavioral Patterns ◽  
Robot Interaction ◽  
Research Activities ◽  
Pattern Approach

HRI designers are faced with the task of creating robots that are easy and pleasant to use for the users. The growing body of research in human–robot interaction (HRI) is still mainly focused on technical aspects of the interaction. It lacks defined guidelines that describe how behavioral expressions for social robots need to be designed to promote high usability and positive user experience. To achieve this goal, we propose to apply the concept of design patterns to HRI. We present a design process that provides step-by-step guidance and methods for HRI designers to generate high quality behavioral patterns for social robots that can be used for different robots and use cases. To document the resulting patterns, we developed a documentation format that provides a clear, standardized structure to note down all relevant aspects of a pattern so that others can understand its design recommendations and apply them to their own robot and use cases. In the present paper, we demonstrate our pattern approach based on an example and describe how we arrived at a pattern language of 40 behavioral patterns that found the basis for future social robot design and related research activities.

Akin: Generating UI Wireframes From UI Design Patterns Using Deep Learning

2021 ◽  
Author(s):  
Nishit Gajjar ◽  
Vinoth Pandian Sermuga Pandian ◽  
Sarah Suleri ◽  
Matthias Jarke
Keyword(s):  
Deep Learning ◽  
Design Patterns ◽  
Ui Design

scholarly journals Usability Studies on Mobile User Interface Design Patterns: A Systematic Literature Review

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
Lumpapun Punchoojit ◽  
Nuttanont Hongwarittorrn
Keyword(s):  
User Interface ◽  
Literature Review ◽  
Mobile Devices ◽  
Systematic Literature Review ◽  
Interaction Design ◽  
Design Patterns ◽  
Mobile User ◽  
Tactile Feedback ◽  
Future Research ◽  
Ui Design

Mobile platforms have called for attention from HCI practitioners, and, ever since 2007, touchscreens have completely changed mobile user interface and interaction design. Some notable differences between mobile devices and desktops include the lack of tactile feedback, ubiquity, limited screen size, small virtual keys, and high demand of visual attention. These differences have caused unprecedented challenges to users. Most of the mobile user interface designs are based on desktop paradigm, but the desktop designs do not fully fit the mobile context. Although mobile devices are becoming an indispensable part of daily lives, true standards for mobile UI design patterns do not exist. This article provides a systematic literature review of the existing studies on mobile UI design patterns. The first objective is to give an overview of recent studies on the mobile designs. The second objective is to provide an analysis on what topics or areas have insufficient information and what factors are concentrated upon. This article will benefit the HCI community in seeing an overview of present works, to shape the future research directions.

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