Generating User Interface from Conceptual, Presentation and User models with JMermaid in a learning approach

2015 ◽  
Author(s):  
Jenny Ruiz ◽  
Gayane Sedrakyan ◽  
Monique Snoeck
Keyword(s):  
User Interface ◽  
Learning Approach ◽  
User Models

scholarly journals Natural Language Understanding for Multi-Level Distributed Intelligent Virtual Sensors

IoT ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 494-505
Author(s):  
Radu-Casian Mihailescu ◽  
Georgios Kyriakou ◽  
Angelos Papangelis
Keyword(s):  
Deep Learning ◽  
User Interface ◽  
Natural Language ◽  
Learning Approach ◽  
Language Understanding ◽  
Virtual Sensor ◽  
Virtual Sensors ◽  
Multi Level ◽  
High Level ◽  
User Friendly

In this paper we address the problem of automatic sensor composition for servicing human-interpretable high-level tasks. To this end, we introduce multi-level distributed intelligent virtual sensors (multi-level DIVS) as an overlay framework for a given mesh of physical and/or virtual sensors already deployed in the environment. The goal for multi-level DIVS is two-fold: (i) to provide a convenient way for the user to specify high-level sensing tasks; (ii) to construct the computational graph that provides the correct output given a specific sensing task. For (i) we resort to a conversational user interface, which is an intuitive and user-friendly manner in which the user can express the sensing problem, i.e., natural language queries, while for (ii) we propose a deep learning approach that establishes the correspondence between the natural language queries and their virtual sensor representation. Finally, we evaluate and demonstrate the feasibility of our approach in the context of a smart city setup.

Intelligent Mobile Learning Systems for Learners with Style

2013 ◽  
pp. 131-149 ◽  
Author(s):  
Tracey J. Mehigan ◽  
Ian Pitt
Keyword(s):  
User Interface ◽  
Learning Environments ◽  
Learning Style ◽  
Mobile Learning ◽  
Learning Systems ◽  
Interface Model ◽  
User Models ◽  
Learning Content ◽  
Research Findings

This chapter discusses the development of intelligent personalized user models for mLearning. Previous research findings are reviewed, indicating that it is possible to identify aspects of a user’s learning style though biometric technologies. A user interface model is presented, designed to intelligently detect the learning-style of individual’s using a mobile learning environments and adapt learning content accordingly. The application of the model to a mLearning system is described.

The Application of a Behavioral Categorization Technique in the Development of User Models

1998 ◽  
Vol 42 (4) ◽  
pp. 434-438
Author(s):  
Robert Bushey ◽  
Jennifer Mitchell Mauney ◽  
Tom Deelman
Keyword(s):  
User Interface ◽  
Performance Measures ◽  
User Interfaces ◽  
Interface Design ◽  
Sales Performance ◽  
Cognitive Measures ◽  
User Models ◽  
Requirements Gathering ◽  
System Requirements ◽  
Determine System

This paper examines a method for the development of new user interfaces for computer systems. The CDM method (Categorizing, Describing, and Modeling method) enhances the requirements gathering phase of user interface design by capitalizing on the concept that the user population has a variety of distinguishable strategies that affect performance. In the CDM method, the user population is first categorized into a reasonable number of groups. The behaviors for each group are described and then this described behavior is qualitatively and quantitatively modeled. These models are used during the system design and operational process to optimize performance for all users. This paper focuses on the first part of the CDM method, namely categorizing users into behaviorally similar groups. Users are categorized based on cognitive measures and sales performance measures. The grouping methodology is then validated based on behavioral data. The CDM method was developed to more accurately determine system requirements for the development of a telecommunications system.

Remote On-Line Control of a High-Voltage in situ Transmission Electron Microscope with A Rational User Interface

1996 ◽  
Vol 54 ◽  
pp. 384-385
Author(s):  
M.A. O’Keefe ◽  
J. Taylor ◽  
D. Owen ◽  
B. Crowley ◽  
K.H. Westmacott ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
User Interface ◽  
Transmission Electron Microscope ◽  
High Voltage ◽  
Materials Science ◽  
Transmission Electron ◽  
On Line ◽  
Electron Microscopes

Remote on-line electron microscopy is rapidly becoming more available as improvements continue to be developed in the software and hardware of interfaces and networks. Scanning electron microscopes have been driven remotely across both wide and local area networks. Initial implementations with transmission electron microscopes have targeted unique facilities like an advanced analytical electron microscope, a biological 3-D IVEM and a HVEM capable of in situ materials science applications. As implementations of on-line transmission electron microscopy become more widespread, it is essential that suitable standards be developed and followed. Two such standards have been proposed for a high-level protocol language for on-line access, and we have proposed a rational graphical user interface. The user interface we present here is based on experience gained with a full-function materials science application providing users of the National Center for Electron Microscopy with remote on-line access to a 1.5MeV Kratos EM-1500 in situ high-voltage transmission electron microscope via existing wide area networks. We have developed and implemented, and are continuing to refine, a set of tools, protocols, and interfaces to run the Kratos EM-1500 on-line for collaborative research. Computer tools for capturing and manipulating real-time video signals are integrated into a standardized user interface that may be used for remote access to any transmission electron microscope equipped with a suitable control computer.

Designing a user interface for a pda-based campus navigation device

2004 ◽  
Author(s):  
Brian Dorn ◽  
Daniel Zelik ◽  
Harisudhakar Vepadharmalingam ◽  
Mayukh Ghosh ◽  
S. Keith Adams
Keyword(s):  
User Interface

When a user interface is good enough: User ratings in UI design

2010 ◽  
Author(s):  
Martin L. Fracker ◽  
Michal Heck ◽  
George Goeschel
Keyword(s):  
User Interface ◽  
Ui Design ◽  
User Ratings
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