scholarly journals Proposal of a Python interface to OpenMI, as the base for open source hydrological framework

2011 ◽  
Vol 7 ◽  
pp. 93-106
Author(s):  
Robert Szczepanek
Keyword(s):  
Open Source ◽  
Programming Languages ◽  
Good Choice ◽  
Hydrological Models ◽  
Department Of Agriculture ◽  
Modeling Framework ◽  
Java Programming ◽  
The Moment ◽  
High Level ◽  
Microsoft Windows

Hydrologists need simple, yet powerful, open source framework for developing and testing mathematical models. Such framework should ensure long-term interoperability and high scalability. This can be done by implementation of the existing, already tested standards. At the moment two interesting options exist: Open Modelling Interface (OpenMI) and Object Modeling System (OMS). OpenMI was developed within the Fifth European Framework Programme for integrated watershed management, described in the Water Framework Directive. OpenMI interfaces are available for the C# and Java programming languages. OpenMI Association is now in the process of agreement with Open Geospatial Consortium (OGC), so the spatial standards existing in OpenMI 2.0 should be better implemented in the future. The OMS project is pure Java, object-oriented modeling framework coordinated by the U.S. Department of Agriculture. Big advantage of OMS compared to OpenMI is its simplicity of implementation. On the other hand, OpenMI seems to be more powerful and better suited for hydrological models. Finally, OpenMI model was selected as the base interface for the proposed open source hydrological framework.  The existing hydrological libraries and models focus usually on just one GIS package (HydroFOSS – GRASS) or one operating system (HydroDesktop – Microsoft Windows). The new hydrological framework should break those limitations. To make hydrological models’ implementation as easy as possible, the framework should be based on a simple, high-level computer language. Low and mid-level languages, like Java (SEXTANTE) or C (GRASS, SAGA) were excluded, as too complicated for regular hydrologist. From popular, high-level languages, Python seems to be a good choice. Leading GIS desktop applications – GRASS and QGIS – use Python as second native language, providing well documented API. This way, a Python-based hydrological library could be easily integrated with any GIS package supporting this programming language. As the OpenMI 2.0 standard supported interfaces only for Java and C#, the Python interface for OpenMI standard, presented in this paper, is the first step done towards the open and interoperable hydrological framework. GIS-related issues of the OpenMI 2.0 standard are also outlined and discussed.

MOSQITO: an open-source and free toolbox for sound quality metrics in the industry and education

2021 ◽  
Vol 263 (5) ◽  
pp. 1164-1175
Author(s):  
Roberto San Millán-Castillo ◽  
Eduardo Latorre-Iglesias ◽  
Martin Glesser ◽  
Salomé Wanty ◽  
Daniel Jiménez-Caminero ◽  
...  
Keyword(s):  
Open Source ◽  
Programming Languages ◽  
Open Source Software ◽  
Objective Assessment ◽  
Sound Quality ◽  
Quality Metrics ◽  
Point Of View ◽  
Wide Range ◽  
Efficient Learning ◽  
High Level

Sound quality metrics provide an objective assessment of the psychoacoustics of sounds. A wide range of metrics has been already standardised while others remain as active research topics. Calculation algorithms are available in commercial equipment or Matlab scripts. However, they may not present available data on general documentation and validation procedures. Moreover, the use of these tools might be unaffordable for some students and independent researchers. In recent years, the scientific and technical community has been developing uncountable open-source software projects in several knowledge fields. The permission to use, study, modify, improve and distribute open-source software make it extremely valuable. It encourages collaboration and sharing, and thus transparency and continuous improvement of the coding. Modular Sound Quality Integrated Toolbox (MOSQITO) project relies on one of the most popular high-level and free programming languages: Python. The main objective of MOSQITO is to provide a unified and modular framework of key sound quality and psychoacoustics metrics, free and open-source, which supports reproducible testing. Moreover, open-source projects can be efficient learning tools at University degrees. This paper presents the current structure of the toolbox from a technical point of view. Besides, it discusses open-source development contributions to graduates training.

scholarly journals fastp: an ultra-fast all-in-one FASTQ preprocessor

2018 ◽  
Author(s):  
Shifu Chen ◽  
Yanqing Zhou ◽  
Yaru Chen ◽  
Jia Gu
Keyword(s):  
Quality Control ◽  
Open Source ◽  
Programming Languages ◽  
Source Code ◽  
Data Filtering ◽  
Quality Filtering ◽  
Downstream Analysis ◽  
High Level ◽  
Unique Molecular Identifier ◽  
Adapter Trimming

AbstractMotivationQuality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming, and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g., Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient.ResultsWe developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality cutting, and many other operations with a single scan of the FASTQ data. It also supports unique molecular identifier preprocessing, poly tail trimming, output splitting, and base correction for paired-end data. It can automatically detect adapters for single-end and paired-end FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools.Availability and ImplementationThe open-source code and corresponding instructions are available at https://github.com/OpenGene/[email protected]

SuperflexPy: a new open source framework for building conceptual hydrological models

2020 ◽  
Author(s):  
Marco Dal Molin ◽  
Dmitri Kavetski ◽  
Fabrizio Fenicia
Keyword(s):  
Open Source ◽  
Model Building ◽  
Essential Element ◽  
Open Science ◽  
Distributed Model ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Modeling Framework ◽  
Flexible Modeling ◽  
Set Up

<p>Hydrological models represent a fundamental tool for linking data with theories in scientific studies. Conceptual models are among the most frequently used type of models in catchment scale studies, due to their low computational requirements and ease of interpretation. Model selection requires the comparison of model alternatives, which is complicated by differences in conceptualization, implementation, and source code availability of the models present in the literature. For this reason, several model-building frameworks have been introduced in the last decade, which facilitate model comparisons by enabling different model alternatives within the same software and numerical architecture. These frameworks, however, have their own limitations, including the difficulty of extension from a user perspective, the requirement of long set-up procedures, and the need of customized input files.<br>Building on the decennial experience with the development and usage of Superflex, a flexible modeling framework for conceptual model building, so far implemented in FORTRAN language and not available as open source, we propose SuperflexPy, an open source Python framework for building conceptual hydrological models. SuperflexPy allows the user to build fully customized models using generic elements (i.e. reservoirs, splitters, junctions, lag functions, etc.) and to arrange them as desired, for example to reflect lumped or semi-distributed model configurations. SuperflexPy is easy to configure through modular initialization scripts, easy to extend with custom functionalities, and easy to interface with other frameworks, making it an essential element for creating a continuous and reproducible pipeline that goes from raw data to model results and interpretation.<br>In this presentation, we will introduce this framework, showcasing some applications and highlighting its potential in the context of open science.</p>

Advances in Stem Instrumentation for Biology

1990 ◽  
Vol 48 (1) ◽  
pp. 362-363
Author(s):  
J. S. Wall
Keyword(s):  
Scanning Transmission Electron Microscope ◽  
Carbon Films ◽  
Specimen Preparation ◽  
Material Deposition ◽  
Active User ◽  
Percent Improvement ◽  
Scanning Transmission ◽  
The Moment ◽  
Film Substrate ◽  
High Level

The forte of the Scanning transmission Electron Microscope (STEM) is high resolution imaging with high contrast on thin specimens, as demonstrated by visualization of single heavy atoms. of equal importance for biology is the efficient utilization of all available signals, permitting low dose imaging of unstained single molecules such as DNA.Our work at Brookhaven has concentrated on: 1) design and construction of instruments optimized for a narrow range of biological applications and 2) use of such instruments in a very active user/collaborator program. Therefore our program is highly interactive with a strong emphasis on producing results which are interpretable with a high level of confidence.The major challenge we face at the moment is specimen preparation. The resolution of the STEM is better than 2.5 A, but measurements of resolution vs. dose level off at a resolution of 20 A at a dose of 10 el/A2 on a well-behaved biological specimen such as TMV (tobacco mosaic virus). To track down this problem we are examining all aspects of specimen preparation: purification of biological material, deposition on the thin film substrate, washing, fast freezing and freeze drying. As we attempt to improve our equipment/technique, we use image analysis of TMV internal controls included in all STEM samples as a monitor sensitive enough to detect even a few percent improvement. For delicate specimens, carbon films can be very harsh-leading to disruption of the sample. Therefore we are developing conducting polymer films as alternative substrates, as described elsewhere in these Proceedings. For specimen preparation studies, we have identified (from our user/collaborator program ) a variety of “canary” specimens, each uniquely sensitive to one particular aspect of sample preparation, so we can attempt to separate the variables involved.

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.

CSim 2

2021 ◽  
Vol 43 (1) ◽  
pp. 1-46
Author(s):  
David Sanan ◽  
Yongwang Zhao ◽  
Shang-Wei Lin ◽  
Liu Yang
Keyword(s):  
Programming Languages ◽  
Concurrent Systems ◽  
Theorem Prover ◽  
Compositional Techniques ◽  
Machine Code ◽  
Top Down ◽  
Hol Theorem Prover ◽  
High Level ◽  
High Degree

To make feasible and scalable the verification of large and complex concurrent systems, it is necessary the use of compositional techniques even at the highest abstraction layers. When focusing on the lowest software abstraction layers, such as the implementation or the machine code, the high level of detail of those layers makes the direct verification of properties very difficult and expensive. It is therefore essential to use techniques allowing to simplify the verification on these layers. One technique to tackle this challenge is top-down verification where by means of simulation properties verified on top layers (representing abstract specifications of a system) are propagated down to the lowest layers (that are an implementation of the top layers). There is no need to say that simulation of concurrent systems implies a greater level of complexity, and having compositional techniques to check simulation between layers is also desirable when seeking for both feasibility and scalability of the refinement verification. In this article, we present CSim 2 a (compositional) rely-guarantee-based framework for the top-down verification of complex concurrent systems in the Isabelle/HOL theorem prover. CSim 2 uses CSimpl, a language with a high degree of expressiveness designed for the specification of concurrent programs. Thanks to its expressibility, CSimpl is able to model many of the features found in real world programming languages like exceptions, assertions, and procedures. CSim 2 provides a framework for the verification of rely-guarantee properties to compositionally reason on CSimpl specifications. Focusing on top-down verification, CSim 2 provides a simulation-based framework for the preservation of CSimpl rely-guarantee properties from specifications to implementations. By using the simulation framework, properties proven on the top layers (abstract specifications) are compositionally propagated down to the lowest layers (source or machine code) in each concurrent component of the system. Finally, we show the usability of CSim 2 by running a case study over two CSimpl specifications of an Arinc-653 communication service. In this case study, we prove a complex property on a specification, and we use CSim 2 to preserve the property on lower abstraction layers.

scholarly journals EXPRESS: Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach

2021 ◽  
pp. 002224372110329
Author(s):  
Nicolas Padilla ◽  
Eva Ascarza
Keyword(s):  
Machine Learning ◽  
Cold Start ◽  
Customer Relationship ◽  
Exponential Families ◽  
Modeling Framework ◽  
Wide Range ◽  
The Moment ◽  
Probabilistic Machine Learning ◽  
Marketing Actions ◽  
Cold Start Problem

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to identify and leverage differences across customers — a very diffcult task when firms attempt to manage new customers, for whom only the first purchase has been observed. For those customers, the lack of repeated observations poses a structural challenge to inferring unobserved differences across them. This is what we call the “cold start” problem of CRM, whereby companies have difficulties leveraging existing data when they attempt to make inferences about customers at the beginning of their relationship. We propose a solution to the cold start problem by developing a probabilistic machine learning modeling framework that leverages the information collected at the moment of acquisition. The main aspect of the model is that it exibly captures latent dimensions that govern the behaviors observed at acquisition as well as future propensities to buy and to respond to marketing actions using deep exponential families. The model can be integrated with a variety of demand specifications and is exible enough to capture a wide range of heterogeneity structures. We validate our approach in a retail context and empirically demonstrate the model's ability at identifying high-value customers as well as those most sensitive to marketing actions, right after their first purchase.

scholarly journals Options for putting CDS/ISIS databases on the internet

2006 ◽  
Vol 40 (3) ◽  
pp. 286-295 ◽  
Author(s):  
Andrew Buxton
Keyword(s):  
Open Source ◽  
Programming Languages ◽  
Operating Systems ◽  
Open Source Software ◽  
Design Methodology ◽  
The Internet ◽  
Content Type

PurposeTo review the variety of software solutions available for putting CDS/ISIS databases on the internet. To help anyone considering which route to take.Design/methodology/approachBriefly describes the characteristics, history, origin and availability of each package. Identifies the type of skills required to implement the package and the kind of application it is suited to. Covers CDS/ISIS Unix version, JavaISIS, IsisWWW, WWWISIS Versions 3 and 5, Genisis, IAH, WWW‐ISIS, and OpenIsis.FindingsThere is no obvious single “best” solution. Several are free but may require more investment in acquiring the skills to install and configure them. The choice will depend on the user's experience with CDS/ISIS formatting language, HTML, programming languages, operating systems, open source software, and so on.Originality/valueThere is detailed documentation available for most of these packages, but little previous guidance to help potential users to distinguish and choose between them.

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