Distributed User Interfaces: State of the Art

Author(s):  
Niklas Elmqvist
Semantic Web ◽  
2021 ◽  
pp. 1-16
Author(s):  
Esko Ikkala ◽  
Eero Hyvönen ◽  
Heikki Rantala ◽  
Mikko Koho

This paper presents a new software framework, Sampo-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the Sampo-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. Sampo-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.


Author(s):  
José Pascual Molina Massó ◽  
Jean Vanderdonckt ◽  
Pascual González López ◽  
Antonio Fernández-Caballero ◽  
María Dolores Lozano Pérez

Author(s):  
Jaymie Strecker ◽  
Atif M. Memon

This chapter describes the state of the art in testing GUI-based software. Traditionally, GUI testing has been performed manually or semimanually, with the aid of capture- replay tools. Since this process may be too slow and ineffective to meet the demands of today’s developers and users, recent research in GUI testing has pushed toward automation. Model-based approaches are being used to generate and execute test cases, implement test oracles, and perform regression testing of GUIs automatically. This chapter shows how research to date has addressed the difficulties of testing GUIs in today’s rapidly evolving technological world, and it points to the many challenges that lie ahead.


Author(s):  
Sha Xin Wei

Since 1984, Graphical User Interfaces have typically relied on visual icons that mimic physical objects like the folder, button, and trash can, or canonical geometric elements like menus, and spreadsheet cells. GUI’s leverage our intuition about the physical environment. But the world can be thought of as being made of stuff as well as things. Making interfaces from this point of view requires a way to simulate the physics of stuff in realtime response to continuous gesture, driven by behavior logic that can be understood by the user and the designer. The author argues for leveraging the corporeal intuition that people learn from birth about heat flow, water, smoke, to develop interfaces at the density of matter that leverage in turn the state of the art in computational physics.


1988 ◽  
Vol 32 (5) ◽  
pp. 259-263
Author(s):  
Michael Good

A major goal of the DECwindows program is to provide a consistent, state-of-the-art user interface for workstation software.1 This interface extends across operating systems and many different types of application programs. Within the DECwindows program we have addressed both the technical and organizational aspects of developing consistent user interfaces across applications. Traditional methods for developing user interface consistency, such as the use of an interface style guide and toolkit, were supplemented with more innovative techniques. An exhibition and catalog of DECwindows application designs helped to develop a DECwindows school of interface design. Electronic conferencing software played an important role in facilitating communication among DECwindows contributors throughout the company. Preliminary user interviews suggest that the DECwindows interface style gives a consistent, usable feel to Digital's workstation applications.


Author(s):  
Habib M. Fardoun ◽  
Sebastián Romero López ◽  
Pedro G. Villanueva

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2075
Author(s):  
Óscar Apolinario-Arzube ◽  
José Antonio García-Díaz ◽  
José Medina-Moreira ◽  
Harry Luna-Aveiga ◽  
Rafael Valencia-García

Automatic satire identification can help to identify texts in which the intended meaning differs from the literal meaning, improving tasks such as sentiment analysis, fake news detection or natural-language user interfaces. Typically, satire identification is performed by training a supervised classifier for finding linguistic clues that can determine whether a text is satirical or not. For this, the state-of-the-art relies on neural networks fed with word embeddings that are capable of learning interesting characteristics regarding the way humans communicate. However, as far as our knowledge goes, there are no comprehensive studies that evaluate these techniques in Spanish in the satire identification domain. Consequently, in this work we evaluate several deep-learning architectures with Spanish pre-trained word-embeddings and compare the results with strong baselines based on term-counting features. This evaluation is performed with two datasets that contain satirical and non-satirical tweets written in two Spanish variants: European Spanish and Mexican Spanish. Our experimentation revealed that term-counting features achieved similar results to deep-learning approaches based on word-embeddings, both outperforming previous results based on linguistic features. Our results suggest that term-counting features and traditional machine learning models provide competitive results regarding automatic satire identification, slightly outperforming state-of-the-art models.


2014 ◽  
Vol 72 (1) ◽  
pp. 111-125 ◽  
Author(s):  
Ricardo Tesoriero ◽  
Pedro G. Villanueva ◽  
Habib M. Fardoun ◽  
Gabriel Sebastián Rivera

2017 ◽  
Vol 18 (4) ◽  
pp. 801-819 ◽  
Author(s):  
Amira Bouabid ◽  
Sophie Lepreux ◽  
Christophe Kolski

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