Virtual reality training systems are commonly used in a variety of domains, and it is important to understand how the realism of a training simulation influences training effectiveness. We conducted ...a controlled experiment to test the effects of display and scenario properties on training effectiveness for a visual scanning task in a simulated urban environment. The experiment varied the levels of field of view and visual complexity during a training phase and then evaluated scanning performance with the simulator's highest levels of fidelity and scene complexity. To assess scanning performance, we measured target detection and adherence to a prescribed strategy. The results show that both field of view and visual complexity significantly affected target detection during training; higher field of view led to better performance and higher visual complexity worsened performance. Additionally, adherence to the prescribed visual scanning strategy during assessment was best when the level of visual complexity during training matched that of the assessment conditions, providing evidence that similar visual complexity was important for learning the technique. The results also demonstrate that task performance during training was not always a sufficient measure of mastery of an instructed technique. That is, if learning a prescribed strategy or skill is the goal of a training exercise, performance in a simulation may not be an appropriate indicator of effectiveness outside of training-evaluation in a more realistic setting may be necessary.
The CCP4 (Collaborative Computational Project, Number 4) software suite for macromolecular structure determination by X‐ray crystallography groups brings together many programs and libraries that, by ...means of well established conventions, interoperate effectively without adhering to strict design guidelines. Because of this inherent flexibility, users are often presented with diverse, even divergent, choices for solving every type of problem. Recently, CCP4 introduced CCP4i2, a modern graphical interface designed to help structural biologists to navigate the process of structure determination, with an emphasis on pipelining and the streamlined presentation of results. In addition, CCP4i2 provides a framework for writing structure‐solution scripts that can be built up incrementally to create increasingly automatic procedures.
CCP4i2 is a graphical user interface to the CCP4 (Collaborative Computational Project, Number 4) software suite and a Python language framework for software automation.
The
CCP
4 (Collaborative Computational Project, Number 4) software suite for macromolecular structure determination by X-ray crystallography groups brings together many programs and libraries that, ...by means of well established conventions, interoperate effectively without adhering to strict design guidelines. Because of this inherent flexibility, users are often presented with diverse, even divergent, choices for solving every type of problem. Recently, CCP4 introduced
CCP
4
i
2, a modern graphical interface designed to help structural biologists to navigate the process of structure determination, with an emphasis on pipelining and the streamlined presentation of results. In addition,
CCP
4
i
2 provides a framework for writing structure-solution scripts that can be built up incrementally to create increasingly automatic procedures.
X‐Seed is a native Microsoft Windows program with three primary functions: (i) to serve as a graphical user interface to the SHELX suite of programs, (ii) to facilitate exploration of crystal packing ...and intermolecular interactions, and (iii) to generate high‐quality molecular graphics artwork suitable for publication and presentation. Development of X‐Seed Version 1.0 began in 1998, when point‐and‐click crystallographic software was still limited in scope and power. Considerable enhancements have been implemented within X‐Seed over the past two decades. Of particular importance are support for the SHELX2019 programs (SHELXS, SHELXD, SHELXT and SHELXL) for structure solution and refinement, and MSRoll for rendering void spaces in crystal structures. The current version (i.e. Version 4) of X‐Seed has a new interface designed to be more interactive and user friendly, and the software can be downloaded and used free of charge.
X‐Seed is still in use after two decades, during which time a number of enhancements have been implemented. It mainly serves as a graphical user interface for SHELX and POV‐Ray, and facilitates exploration of crystal packing.
The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various ...neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).
ShelXle: a Qt graphical user interface for SHELXL Hübschle, Christian B.; Sheldrick, George M.; Dittrich, Birger
Journal of applied crystallography,
December 2011, Letnik:
44, Številka:
6
Journal Article
Recenzirano
Odprti dostop
ShelXle is a graphical user interface for SHELXL Sheldrick, G. M. (2008). Acta Cryst. A64, 112–122, currently the most widely used program for small‐molecule structure refinement. It combines an ...editor with syntax highlighting for the SHELXL‐associated .ins (input) and .res (output) files with an interactive graphical display for visualization of a three‐dimensional structure including the electron density (Fo) and difference density (Fo–Fc) maps. Special features of ShelXle include intuitive atom (re‐)naming, a strongly coupled editor, structure visualization in various mono and stereo modes, and a novel way of displaying disorder extending over special positions. ShelXle is completely compatible with all features of SHELXL and is written entirely in C++ using the Qt4 and FFTW libraries. It is available at no cost for Windows, Linux and Mac‐OS X and as source code.
It is common practice for developers of user-facing software to transform a mock-up of a graphical user interface (GUI) into code. This process takes place both at an application's inception and in ...an evolutionary context as GUI changes keep pace with evolving features. Unfortunately, this practice is challenging and time-consuming. In this paper, we present an approach that automates this process by enabling accurate prototyping of GUIs via three tasks: detection, classification, and assembly. First, logical components of a GUI are detected from a mock-up artifact using either computer vision techniques or mock-up metadata. Then, software repository mining, automated dynamic analysis, and deep convolutional neural networks are utilized to accurately classify GUI-components into domain-specific types (e.g., toggle-button). Finally, a data-driven, K-nearest-neighbors algorithm generates a suitable hierarchical GUI structure from which a prototype application can be automatically assembled. We implemented this approach for Android in a system called ReDraw. Our evaluation illustrates that ReDraw achieves an average GUI-component classification accuracy of 91 percent and assembles prototype applications that closely mirror target mock-ups in terms of visual affinity while exhibiting reasonable code structure. Interviews with industrial practitioners illustrate ReDraw's potential to improve real development workflows.
We introduce MultiPiles, a visualization to explore time‐series of dense, weighted networks. MultiPiles is based on the physical analogy of piling adjacency matrices, each one representing a single ...temporal snapshot. Common interfaces for visualizing dynamic networks use techniques such as: flipping/animation; small multiples; or summary views in isolation. Our proposed ‘piling’ metaphor presents a hybrid of these techniques, leveraging each one's advantages, as well as offering the ability to scale to networks with hundreds of temporal snapshots. While the MultiPiles technique is applicable to many domains, our prototype was initially designed to help neuroscientists investigate changes in brain connectivity networks over several hundred snapshots. The piling metaphor and associated interaction and visual encodings allowed neuroscientists to explore their data, prior to a statistical analysis. They detected high‐level temporal patterns in individual networks and this helped them to formulate and reject several hypotheses.
Recent improvements in DSR Kratzert, Daniel; Krossing, Ingo
Journal of applied crystallography,
June 2018, Letnik:
51, Številka:
3
Journal Article
Recenzirano
The DSR computer program has received many minor and major updates over the past two years. This publication describes some new features, such as disorder modelling on special positions, error ...detection for restraints and trifluoromethyl group modelling. Most importantly, the graphical user interfaces (GUIs) make DSR a lot easier to use, especially in modelling disorder on special positions that would have been difficult to implement without a GUI. In addition, generating and editing of new fragments in the database is now much easier.
This article describes recent developments in the computer program DSR. In particular, improvements have been made to the graphical user interface, and to the avoidance of operating errors by recognizing them.
The graphical user interface (GUI) has become the prime means for interacting with computing systems. It leverages human perceptual and motor capabilities for elementary tasks such as command ...exploration and invocation, information search, and multitasking. For designing a GUI, numerous interconnected decisions must be made such that the outcome strikes a balance between human factors and technical objectives. Normally, design choices are specified manually and coded within the software by professional designers and developers. This article surveys combinatorial optimization as a flexible and powerful tool for computational generation and adaptation of GUIs. As recently as 15 years ago, applications were limited to keyboards and widget layouts. The obstacle has been the mathematical definition of design tasks, on the one hand, and the lack of objective functions that capture essential aspects of human behavior, on the other. This article presents definitions of layout design problems as integer programming tasks, a coherent formalism that permits identification of problem types, analysis of their complexity, and exploitation of known algorithmic solutions. It then surveys advances in formulating evaluative functions for common design-goal foci such as user performance and experience. The convergence of these two advances has expanded the range of solvable problems. Approaches to practical deployment are outlined with a wide spectrum of applications. This article concludes by discussing the position of this application area within optimization and human-computer interaction research and outlines challenges for future work.
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