When students are learning to develop algorithms, they very often spend more time dealing with issues of syntax than solving the problem. Additionally, the textual nature of most programming environments works against...
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When students are learning to develop algorithms, they very often spend more time dealing with issues of syntax than solving the problem. Additionally, the textual nature of most programming environments works against the learning style of the majority of students. RAPTOR is a flowchart-based programming environment, designed specifically to help students visualize their algorithms and avoid syntactic baggage. RAPTOR programs are created visually and executed visually by tracing the execution through the flowchart. Required syntax is kept to a minimum. Students preferred using flowcharts to express their algorithms, and were more successful creating algorithms using RAPTOR than using a traditional language or writing flowcharts without RAPTOR.
VisPro is a general-purpose visual language generation system based on Reserved Graph Grammar (RGG). It can express a wide range of diagrammatic visual programming languages (VPLs). This paper presents a global layout...
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ISBN:
(纸本)0909925895
VisPro is a general-purpose visual language generation system based on Reserved Graph Grammar (RGG). It can express a wide range of diagrammatic visual programming languages (VPLs). This paper presents a global layout approach used in the VisPro system. Our approach is grammar-based graph drawing, in which layout rules are embedded in the productions of RGG. Thus, the RGG formalism serves both the visual language grammar and the layout grammar. This approach is appropriate and feasible enough for graph drawing in the area of visual programming languages based on reserved graph grammars.
The analysis of raw data in neuroimaging has become a computationally entrenched process with many intricate steps run on increasingly larger datasets. Many software packages exist that provide either complete analyse...
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The analysis of raw data in neuroimaging has become a computationally entrenched process with many intricate steps run on increasingly larger datasets. Many software packages exist that provide either complete analyses or specific steps in an analysis. These packages often possess diverse input and output requirements, utilize different file formats, run in particular environments, and have limited abilities with certain types of data. The combination of these packages to achieve more sensitive and accurate results has become a common tactic in brain mapping studies but requires much work to ensure valid interoperation between programs. The handling, organization, and storage of intermediate data can prove difficult as well. The LONI Pipeline Processing Environment is a simple, efficient, and distributed computing solution to these problems enabling software inclusion from different laboratories in different environments. It is used here to derive a T1-weighted MRI atlas of the human brain from 452 normal young adult subjects with fully automated processing. The LONI Pipeline Processing Environment's parallel processing efficiency using an integrated client/server dataflow model was 80.9% when running the atlas generation pipeline from a PC client (Acer TravelMate 340T) on 48 dedicated server processors (Silicon Graphics Inc. Origin 3000). The environment was 97.5% efficient when the same analysis was run on eight dedicated processors. (C) 2003 Elsevier Science (USA). All rights reserved.
In visualising multidimensional data, it is well known that different types of data require different types of algorithms to process them. Data sets might be distinguished according to volume, variable types and distr...
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ISBN:
(纸本)0780381548
In visualising multidimensional data, it is well known that different types of data require different types of algorithms to process them. Data sets might be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This suggests that hybrid combinations of appropriate algorithms might also successfully address other characteristics of data. This paper presents a system and framework in which a user can easily explore hybrid algorithms and the data flowing through them. visual programming and a novel algorithmic architecture let the user semi-automatically define data flows and the co-ordination of multiple views.
Analyzing the power system network is becoming difficult task because of the volume of data that must be examined. A more serious problem than the over massive of data in analyzing the power system is the manner in wh...
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ISBN:
(纸本)0780379896
Analyzing the power system network is becoming difficult task because of the volume of data that must be examined. A more serious problem than the over massive of data in analyzing the power system is the manner in which data is presented. It is difficult to visualize an electrical network by examining tabular data output. Converting the data into computer graphic presentations has solved many similar problems. The user will be able to discover problems in the network much faster and easier than traditional methods have previously allowed.
This paper proposes a conceptual model called compound brushing for modeling the brushing techniques used in dynamic data visualization. In this approach brushing techniques are modeled as higraphs with five types of ...
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ISBN:
(纸本)0780381548
This paper proposes a conceptual model called compound brushing for modeling the brushing techniques used in dynamic data visualization. In this approach brushing techniques are modeled as higraphs with five types of basic entities: data, selection, device, renderer, and transformation. Using this model, a flexible visual programming tool is designed not only to configure/control various common types of brushing techniques currently used in dynamic data visualization, but also to investigate new brushing techniques.
The implementation of visual languages requires a wide range of conceptual and technical knowledge from issues of user interface design and graphical implementation to aspects of analysis and transformation for langua...
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The implementation of visual languages requires a wide range of conceptual and technical knowledge from issues of user interface design and graphical implementation to aspects of analysis and transformation for languages in general. We present a powerful toolset that incorporates such knowledge. Our toolset generates editors from high-level specifications. A language is specified by identifying certain patterns in the language structure and selecting a visual representation from a set of precoined solutions. visual programs are represented by attributed abstract trees. Therefore, further phases of processing visual programs can be generated by state-of-the-art tools for language implementation. We demonstrate that even challenging visual languages can be implemented with reasonably little effort and with rather limited technical knowledge. The approach is suitable for a large variety of visual language styles. Copyright (C) 2003 John Wiley Sons, Ltd.
Data can be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. This has led to a...
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Data can be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. This has led to an abundance of often disparate algorithmic techniques. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This paper presents a system and framework in which a user can easily explore algorithms as well as their hybrid conjunctions and the data flowing through them. visual programming and a novel algorithmic architecture let the user semi-automatically define data-flows and the coordination of multiple views of algorithmic and visualisation components. We propose that our approach has two main benefits: significant improvements in run times of MDS algorithms can be achieved, and intermediate views of the data and the visualisation program structure can provide greater insight and control over the visualisation process.
Many visual programming languages (VPLs) rely on the data-flow paradigm, probably because of its simple and intuitive functioning mechanism. However, there are cases where more powerful programming constructs are need...
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Many visual programming languages (VPLs) rely on the data-flow paradigm, probably because of its simple and intuitive functioning mechanism. However, there are cases where more powerful programming constructs are needed to deal with complex problems. For example, iteration is undoubtedly an important aspect of programming, and should allow repetitive behaviors to be specified in compact and easy ways. Most existing data-flow VPLs provide special constructs to implement iterations, therefore infringing the pure data-flow paradigm in favor of program simplicity, This paper has three main purposes: (1) To provide a survey of the mechanisms used by some representative data-flow VPLs to carry out iterations;(2) To investigate, given a pure data-flow VPL, what should be the minimum set of characteristics which, after being added to the VPL, allow iterations to be implemented;and (3) To show real data-flow iteration implementations which rely on the characteristics pertaining to such a minimum set. (C) 2001 Elsevier Science Ltd. All rights reserved.
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