scholarly journals Short communication: The Topographic Analysis Kit (TAK) for TopoToolbox

2018 ◽  
Author(s):  
Adam M. Forte ◽  
Kelin X. Whipple
Keyword(s):  
Open Source ◽  
Domain Knowledge ◽  
Building Blocks ◽  
Topographic Analysis ◽  
Runtime Environment ◽  
Computing Environments ◽  
Programming Skills ◽  
High Level ◽  
Effective Use ◽  
Channel Steepness

Abstract. Quantitative analysis of digital topographic data is an increasingly important part of many studies in the geosciences. Initially, performing these analyses was a niche endeavor, requiring detailed domain knowledge and programming skills, but increasingly broad, flexible, open source code bases have been developed to increasingly democratize topographic analysis. However, many of these still require specific computing environments and/or moderate levels of knowledge of both the relevant programming language and the correct way to take these fundamental building blocks and conduct an efficient and effective topographic analysis. To partially address this, we have written the Topographic Analysis Kit (TAK) which leverages the power of one of these open source libraries, TopoToolbox, to build a series of high-level topographic analysis tools to perform a variety of common topographic analyses, including generation of maps of normalized channel steepness or chi and selection and statistical analysis of populations of watersheds. No programming skills or advanced Matlab capability is required for effective use of TAK. In addition, to expand the utility of TAK, along with the primary functions, which like the underlying TopoToolbox functions require Matlab and several proprietary toolboxes to run, we provide compiled versions of these functions that use the free Matlab Runtime Environment for users who do not have institutional access to Matlab or all of the required toolboxes.

scholarly journals Short communication: The Topographic Analysis Kit (TAK) for TopoToolbox

2019 ◽  
Vol 7 (1) ◽  
pp. 87-95 ◽  
Author(s):  
Adam M. Forte ◽  
Kelin X. Whipple
Keyword(s):  
Domain Knowledge ◽  
Short Communication ◽  
Building Blocks ◽  
Topographic Analysis ◽  
Runtime Environment ◽  
Computing Environments ◽  
Programming Skills ◽  
High Level ◽  
Effective Use ◽  
Channel Steepness

Abstract. Quantitative analysis of digital topographic data is an increasingly important part of many studies in the geosciences. Initially, performing these analyses was a niche endeavor, requiring detailed domain knowledge and programming skills, but increasingly broad, flexible, open-source code bases have been developed to increasingly democratize topographic analysis. However, many of these analyses still require specific computing environments and/or moderate levels of knowledge of both the relevant programming language and the correct way to take these fundamental building blocks and conduct an efficient and effective topographic analysis. To partially address this, we have written the Topographic Analysis Kit (TAK), which leverages the power of one of these open code bases, TopoToolbox, to build a series of high-level topographic analysis tools to perform a variety of common topographic analyses. These analyses include the generation of maps of normalized channel steepness, or χ, and selection and statistical analysis of populations of watersheds. No programming skills or advanced mastery of MATLAB is required for effective use of TAK. In addition – to expand the utility of TAK along with the primary functions, which like the underlying TopoToolbox functions require MATLAB and several proprietary toolboxes to run – we provide compiled versions of these functions that use the free MATLAB Runtime Environment for users who do not have institutional access to MATLAB or all of the required toolboxes.

scholarly journals SDN Programming for Heterogeneous Switches with Flow Table Pipelining

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Junchang Wang ◽  
Shaojin Cheng ◽  
Xiong Fu
Keyword(s):  
Building Blocks ◽  
Flow Rule ◽  
Link Failures ◽  
Flow Table ◽  
Network Link ◽  
Rule Sets ◽  
Rule Set ◽  
State Changes ◽  
High Level ◽  
Effective Use

High-level programming is one of the critical building blocks of the effective use of software-defined networking (SDN). Existing solutions, however, either (1) cannot utilize the state-of-the-art switches with flow table pipelining, a key technique to prevent flow rule set explosion or (2) force programmers to manually organize and manage hardware flow table pipelines, which is time-consuming and error-prone. This paper presents a high-level SDN programming framework to address these issues. The framework can automatically (1) generate rule sets for heterogeneous switches with different flow table pipelining designs and (2) update installed rules when the network state changes. As a result, the framework can not only generate efficient rule sets for switches but also provide programmers a centralized, intuitive, and hence easy-to-use programming API. Experiments show that the framework can generate compact rule sets that are 29–116 times smaller than those generated by other open-source SDN controllers. Besides, the framework is 5 times faster to recover from network link failures in comparison to other controllers.

scholarly journals Identification of biological mechanisms by semantic classifier systems

2018 ◽  
Author(s):  
Ludwig Lausser ◽  
Florian Schmid ◽  
Lea Siegle ◽  
Rolf Hühne ◽  
Malte Buchholz ◽  
...  
Keyword(s):  
Data Mining ◽  
Domain Knowledge ◽  
De Novo ◽  
Building Blocks ◽  
Classification Model ◽  
Biological Knowledge ◽  
Classifier Systems ◽  
Semantic Approach ◽  
Classifier System ◽  
High Level

AbstractThe interpretability of a classification model is one of its most essential characteristics. It allows for the generation of new hypotheses on the molecular background of a disease. However, it is questionable if more complex molecular regulations can be reconstructed from such limited sets of data. To bridge the gap between complexity and interpretability, we replace the de novo reconstruction of these processes by a hybrid classification approach partially based on existing domain knowledge. Using semantic building blocks that reflect real biological processes these models were able to construct hypotheses on the underlying genetic configuration of the analysed phenotypes. As in the building process, also these hypotheses are composed of high-level biology-based terms. The semantic information we utilise from gene ontology is a vocabulary which comprises the essential processes or components of a biological system. The constructed semantic multi-classifier system consists of expert base classifiers which each select the most suitable term for characterising their assigned problems. Our experiments conducted on datasets of three distinct research fields revealed terms with well-known associations to the analysed context. Furthermore, some of the chosen terms do not seem to be obviously related to the issue and thus lead to new, hypotheses to pursue.Author summaryData mining strategies are designed for an unbiased de novo analysis of large sample collections and aim at the detection of frequent patterns or relationships. Later on, the gained information can be used to characterise diagnostically relevant classes and for providing hints to the underlying mechanisms which may cause a specific phenotype or disease. However, the practical use of data mining techniques can be restricted by the available resources and might not correctly reconstruct complex relationships such as signalling pathways.To counteract this, we devised a semantic approach to the issue: a multi-classifier system which incorporates existing biological knowledge and returns interpretable models based on these high-level semantic terms. As a novel feature, these models also allow for qualitative analysis and hypothesis generation on the molecular processes and their relationships leading to different phenotypes or diseases.

Generic tasks as building blocks for knowledge-based systems: the diagnosis and routine design examples

1988 ◽  
Vol 3 (3) ◽  
pp. 183-210 ◽  
Author(s):  
B. Chandrasekaran
Keyword(s):  
Problem Solving ◽  
Domain Knowledge ◽  
Building Blocks ◽  
Knowledge Based Systems ◽  
Diagnostic Systems ◽  
Planning Systems ◽  
Knowledge Based ◽  
Generic Tasks ◽  
High Level ◽  
And Control

AbstractThe level of abstraction of much of the work in knowledge-based systems (the rule, frame, logic level) is too low to provide a rich enough vocabulary for knowledge and control. I provide an overview of a framework called the Generic Task approach that proposes that knowledge systems should be built out of building blocks, each of which is appropriate for a basic type of problem solving. Each generic task uses forms of knowledge and control strategies that are characteristic to it, and are in general conceptually closer to domain knowledge. This facilitates knowledge acquisition and can produce a more perspicuous explanation of problem solving. The relationship of the constructs at the generic task level to the rule-frame level is analogous to that between high-level programming languages and assembly languages in computer science. I describe a set of generic tasks that have been found particularly useful in constructing diagnostic, design and planning systems. In particular, I describe two tools, CSRL and DSPL, that are useful for building classification-based diagnostic systems and skeletal planning systems respectively, and a high level toolbox that is under construction called the Generic Task toolbox.

Promoting Hybrid Learning through an Open Source EBook Approach

2010 ◽  
Vol 14 (3) ◽  
Author(s):  
Xin Bai ◽  
Michael B. Smith
Keyword(s):  
Open Source ◽  
Building Blocks ◽  
Educational Technologies ◽  
Just In Time ◽  
Learning Modules ◽  
Learning Content ◽  
Long Run ◽  
E Learning ◽  
Teaching Efficiency ◽  
Content Design

Educational technology is developing rapidly, making education more accessible, affordable, adaptable, and equitable. Students now have the option to choose a campus that can provide excellent blended learning curriculum with minimal geographical restraints. We proactively explore ways to maximize the power of educational technologies to increase enrollment, reduce failure rates, improve teaching efficiency, and cut costs without sacrificing high quality or placing extra burden on faculty. This mission is accomplished through open source learning content design and development. We developed scalable, shareable, and sustainable e-learning modules as book chapters that can be distributed through both computers and mobile devices. The resulting e-learning building blocks can automate the assessment processes, provide just-in-time feedback, and adjust the teaching material dynamically based upon each student’s strengths and weaknesses. Once built, these self-contained learning modules can be easily maintained, shared, and re-purposed, thus cutting costs in the long run. This will encourage faculty from different disciplines to share their best teaching practices online. The end result of the project is a sustainable knowledge base that can grow over time, benefit all the discipline, and promote learning.

scholarly journals An Open-Source Scale Model Platform for Teaching Autonomous Vehicle Technologies

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3850
Author(s):  
Bastien Vincke ◽  
Sergio Rodriguez Rodriguez Florez ◽  
Pascal Aubert
Keyword(s):  
Open Source ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Constrained Systems ◽  
Scale Model ◽  
Technical Students ◽  
Vehicle Technologies ◽  
Model Platform ◽  
High Level ◽  
Time And Energy

Emerging technologies in the context of Autonomous Vehicles (AV) have drastically evolved the industry’s qualification requirements. AVs incorporate complex perception and control systems. Teaching the associated skills that are necessary for the analysis of such systems becomes a very difficult process and existing solutions do not facilitate learning. In this study, our efforts are devoted to proposingan open-source scale model vehicle platform that is designed for teaching the fundamental concepts of autonomous vehicles technologies that are adapted to undergraduate and technical students. The proposed platform is as realistic as possible in order to present and address all of the fundamental concepts that are associated with AV. It includes all on-board components of a stand-alone system, including low and high level functions. Such functionalities are detailed and a proof of concept prototype is presented. A set of experiments is carried out, and the results obtained using this prototype validate the usability of the model for the analysis of time- and energy-constrained systems, as well as distributed embedded perception systems.

scholarly journals E-learning-Oriented Software Architecture Design and Case Study

2015 ◽  
Vol 10 (4) ◽  
pp. 59
Author(s):  
Peng Lu ◽  
Xiao Cong ◽  
Dongdai Zhou
Keyword(s):  
Software Architecture ◽  
Building Blocks ◽  
Domain Model ◽  
Learning System ◽  
Application Framework ◽  
Component Library ◽  
E Learning ◽  
The Difference ◽  
High Level

Nowadays, E-learning system has been widely applied to practical teaching. It was favored by people for its characterized course arrangement and flexible learning schedule. However, the system does have some problems in the process of application such as the functions of single software are not diversified enough to satisfy the requirements in teaching completely. In order to cater more applications in the teaching process, it is necessary to integrate functions from different systems. But the difference in developing techniques and the inflexibility in design makes it difficult to implement. The major reason of these problems is the lack of fine software architecture. In this article, we build domain model and component model of E-learning system and components integration method on the basis of WebService. And we proposed an abstract framework of E-learning which could express the semantic relationship among components and realize high level reusable on the basis of informationized teaching mode. On this foundation, we form an E-learning oriented layering software architecture contain component library layer, application framework layer and application layer. Moreover, the system contains layer division multiplexing and was not built upon developing language and tools. Under the help of the software architecture, we could build characterized E-learning system flexibly like building blocks through framework selection, component assembling and replacement. In addition, we exemplify how to build concrete E-learning system on the basis of this software architecture.

Open source software as a mature library system in Armenia

Infolib ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 34-37
Author(s):  
Anna Chulyan ◽  
Keyword(s):  
Cultural Heritage ◽  
Open Source ◽  
Open Source Software ◽  
New Technologies ◽  
Digital Preservation ◽  
Free Access ◽  
Efficient Organization ◽  
Digital Repositories ◽  
High Level

The article touches upon the importance of long-term digital preservation of Armenian cultural heritage through creation of digital repositories using Open-Source Software in Armenian libraries. The research highlights the advantages of Open-Source Software in context of providing free access to digital materials, as well as its high level of functionality in order to empower libraries with new technologies for more efficient organization and dissemination of information.

An open-source program to analyze spontaneous sympathetic neurohemodynamic transduction

2021 ◽  
Vol 125 (3) ◽  
pp. 972-976
Author(s):  
Myles W. O’Brien ◽  
Jennifer L. Petterson ◽  
Derek S. Kimmerly
Keyword(s):  
Open Source ◽  
Sympathetic Nerve Activity ◽  
Muscle Sympathetic Nerve Activity ◽  
Analysis Program ◽  
Microsoft Excel ◽  
Nerve Activity ◽  
Source Program ◽  
Pressor Responses ◽  
Sympathetic Regulation ◽  
High Level

The pressor responses to spontaneous bursts of muscle sympathetic nerve activity provide important information regarding sympathetic regulation of the circulation. Many laboratories worldwide quantify sympathetic neurohemodynamic transduction using in-house, customized software requiring high-level programming skills and/or costly computer programs. To overcome these barriers, this study presents a simple, open-source, Microsoft Excel-based analysis program along with video instructions to assist researchers without the necessary resources to quantify sympathetic neurohemodynamic transduction.

scholarly journals Composition, Separation of Roles and Model-Driven Approaches as Enabler of a Robotics Software Ecosystem

2020 ◽  
pp. 53-108
Author(s):  
Christian Schlegel ◽  
Alex Lotz ◽  
Matthias Lutz ◽  
Dennis Stampfer
Keyword(s):  
Complex Systems ◽  
Open Source ◽  
Building Block ◽  
Building Blocks ◽  
Software Systems ◽  
Software Components ◽  
Separation Of Concerns ◽  
Software Ecosystem ◽  
Model Driven ◽  
Successful Approach

AbstractSuccessful engineering principles for building software systems rely on the separation of concerns for mastering complexity. However, just working on different concerns of a system in a collaborative way is not good enough for economically feasible tailored solutions. A successful approach for this is the composition of complex systems out of commodity building blocks. These come as is and can be represented as blocks with ports via data sheets. Data sheets are models and allow a proper selection and configuration as well as the prediction of the behavior of a building block in a specific context. This chapter explains how model-driven approaches can be used to support separation of roles and composition for robotics software systems. The models, open-source tools, open-source robotics software components and fully deployable robotics software systems shape a robotics software ecosystem.

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