IMPLEMENTING FUNCTIONAL MODULARITY FOR PROCESSING OF GENERAL PHOTOGRAMMETRIC DATA WITH THE DAMPED BUNDLE ADJUSTMENT TOOLBOX (DBAT)

Abstract. The Damped Bundle Adjustment Toolbox (DBAT) is a free, open-source, toolbox for bundle adjustment. The purpose of DBAT is to provide an independent, open-source toolkit for statistically rigorous bundle adjustment computations. The capabilities include bundle adjustment, network analysis, point filtering, forward intersection, spatial intersection, plotting functions, and computations of quality indicators such as posterior covariance estimates and parameter correlations. DBAT is written in the high-level Matlab language and includes several processing example files. The input formats have so far been restricted to PhotoModeler export files and Photoscan (Metashape) native files. Fine-tuning of the processing has so far required knowledge of the Matlab language.This paper describes the development of a scripting language based on the XML (eXtensible Markup Language) language that allow the user a fine-grained control over what operations are applied to the input data, while keeping the needed programming skills at a minimum. Furthermore, the scripting language allows a wide range of input formats. Additionally, the XML format allows simple extension of the script file format both in terms of adding new operations, file formats, or adding parameters to existing operations. Overall, the script files will in principle allow DBAT to process any kind of photogrammetric input and should extend the usability of DBAT as a scientific and teaching tool for photogrammetric computations.

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Vcfanno: fast, flexible annotation of genetic variants

10.1101/041863 ◽

2016 ◽

Author(s):

Brent S. Pedersen ◽

Ryan M. Layer ◽

Aaron R. Quinlan

Keyword(s):

Genetic Variants ◽

Source Code ◽

Variant Annotation ◽

Link Type ◽

File Formats ◽

Whole Exome ◽

Wide Range ◽

Reference Databases ◽

Scripting Language ◽

Genome Annotations

ABSTRACTBackgroundThe integration of genome annotations and reference databases is critical to the identification of genetic variants that may be of interest in studies of disease or other traits. However, comprehensive variant annotation with diverse file formats is difficult with existing methods.ResultsWe have developed vcfanno as a flexible toolset that simplifies the annotation of genetic variants in VCF format. Vcfanno can extract and summarize multiple attributes from one or more annotation files and append the resulting annotations to the INFO field of the original VCF file. Vcfanno also integrates the lua scripting language so that users can easily develop custom annotations and metrics. By leveraging a new parallel “chromosome sweeping” algorithm, it enables rapid annotation of both whole-exome and whole-genome datasets. We demonstrate this performance by annotating over 85.3 million variants in less than 17 minutes (>85,000 variants per second) with 50 attributes from 17 commonly used genome annotation resources.ConclusionsVcfanno is a flexible software package that provides researchers with the ability to annotate genetic variation with a wide range of datasets and reference databases in diverse genomic formats.AvailabilityThe vcfanno source code is available at https://github.com/brentp/vcfanno under the MIT license, and platform-specific binaries are available at https://github.com/brentp/vcfanno/releases. Detailed documentation is available at http://brentp.github.io/vcfanno/, and the code underlying the analyses presented can be found at https://github.com/brentp/vcfanno/tree/master/scripts/paper.

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

INTER-NOISE and NOISE-CON Congress and Conference Proceedings ◽

10.3397/in-2021-1767 ◽

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.

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CPPE: An Open-Source C++ and Python Library for Polarizable Embedding

10.26434/chemrxiv.8949101 ◽

2019 ◽

Author(s):

Maximilian Scheurer ◽

Peter Reinholdt ◽

Erik Kjellgren ◽

Jógvan Magnus Haugaard Olsen ◽

Andreas Dreuw ◽

...

Keyword(s):

Rapid Prototyping ◽

Open Source ◽

Quantum Chemical ◽

Programming Effort ◽

Scripting Language ◽

Computational Spectroscopy ◽

High Level ◽

Polarizable Embedding ◽

The Way

We present a modular open-source library for polarizable embedding (PE) named CPPE. The library is implemented in C++, and it additionally provides a Python interface for rapid prototyping and experimentation in a high-level scripting language. Our library integrates seamlessly with existing quantum chemical program packages through an intuitive and minimal interface. Until now, CPPE has been interfaced to three packages, Q-Chem, Psi4, and PySCF. Furthermore, we show CPPE in action using all three program packages for a computational spectroscopy application. With CPPE, host program interfaces only require minor programming effort, paving the way for new combined methodologies and broader availability of the PE model.<br>

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Two-Level Attentions and Grouping Attention Convolutional Network for Fine-Grained Image Classification

Applied Sciences ◽

10.3390/app9091939 ◽

2019 ◽

Vol 9 (9) ◽

pp. 1939 ◽

Cited By ~ 5

Author(s):

Yadong Yang ◽

Xiaofeng Wang ◽

Quan Zhao ◽

Tingting Sui

Keyword(s):

Image Classification ◽

Feature Fusion ◽

Recognition Rate ◽

Fine Tuning ◽

Semantic Features ◽

Convolutional Network ◽

Attention Model ◽

Fine Grained ◽

Visual Attention Mechanism ◽

High Level

The focus of fine-grained image classification tasks is to ignore interference information and grasp local features. This challenge is what the visual attention mechanism excels at. Firstly, we have constructed a two-level attention convolutional network, which characterizes the object-level attention and the pixel-level attention. Then, we combine the two kinds of attention through a second-order response transform algorithm. Furthermore, we propose a clustering-based grouping attention model, which implies the part-level attention. The grouping attention method is to stretch all the semantic features, in a deeper convolution layer of the network, into vectors. These vectors are clustered by a vector dot product, and each category represents a special semantic. The grouping attention algorithm implements the functions of group convolution and feature clustering, which can greatly reduce the network parameters and improve the recognition rate and interpretability of the network. Finally, the low-level visual features and high-level semantic information are merged by a multi-level feature fusion method to accurately classify fine-grained images. We have achieved good results without using pre-training networks and fine-tuning techniques.

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CPPE: An Open-Source C++ and Python Library for Polarizable Embedding

10.26434/chemrxiv.8949101.v1 ◽

2019 ◽

Author(s):

Maximilian Scheurer ◽

Peter Reinholdt ◽

Erik Kjellgren ◽

Jógvan Magnus Haugaard Olsen ◽

Andreas Dreuw ◽

...

Keyword(s):

Rapid Prototyping ◽

Open Source ◽

Quantum Chemical ◽

Programming Effort ◽

Scripting Language ◽

Computational Spectroscopy ◽

High Level ◽

Polarizable Embedding ◽

The Way

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Open Source Software Library for Thermo-Hydro-Mechanical Coupled Processes in Python

Safety of Nuclear Waste Disposal ◽

10.5194/sand-1-185-2021 ◽

2021 ◽

Vol 1 ◽

pp. 185-186

Author(s):

Carsten Rücker

Keyword(s):

Open Source ◽

Open Source Software ◽

Site Selection ◽

Selection Process ◽

Fluid Motion ◽

Coupled Processes ◽

Software Library ◽

Source Codes ◽

Scripting Language ◽

High Level

Abstract. This contributed poster shows the current state of development of a finite element implementation as part of an open source software library (OSSL) for the simulation of thermo-hydro-mechanical (THM) coupled processes. The reliable handling of numerical methods is fundamental for the understanding of scientific interrelationships and thus, a crucial prerequisite for modeling THM scenarios, as well as for the understanding and evaluation of preliminary safety investigations during the site selection process for the storage of high-level radioactive waste. There are several motivations for developing an in-house OSSL, which will allow us to: Build capacity and maintenance within BASE (Federal Office for the Safety of Nuclear Waste Management) regarding issues of the numerical modeling of safety-relevant aspects on the long-term safety analyses specified by the German legislator in the site selection process. Develop a collection of known benchmarks and evaluation examples for the comparison of different software tools, applying a uniform interface to simplify the use of the available highly specialized open source codes. Diversify the testing possibilities regarding the preliminary safety investigations by means of our own, independent modeling software. Document basic THM scenarios for internal or, if necessary, public technical training, e.g., density-driven fluid flow (Fig. 1), convergence in salt, temperature propagation in the repository area, crack development, diffusive or advective mass transport. Ensure transparency and, in principle, might allow for appropriately proven-quality (validated) and documented simulation tools for the public regarding questions about the preliminary safety investigations during the site selection process. The development of the OSSL is mainly based on the scripting language Python, which allows the necessary flexibility for the diverse fields of application and at the same time enables maximum transparency for all aspects of the source code. To ensure the high quality of the software, state of the art development tools are used (e.g., version control, automated tests, and documentation generation). Figure 1 shows our preliminary simulation results of the so-called Elder problem (Elder, 1967), a popular standard benchmark for thermo-hydrogeological coupling in which fluid motion in a porous medium is driven by buoyancy forces.

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Low-Strength Self-Compacting Concrete

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.259.97 ◽

2017 ◽

Vol 259 ◽

pp. 97-100

Author(s):

Lucia Osuská ◽

Martin Labaj ◽

Jaroslav Valek

Keyword(s):

Rheological Properties ◽

Fine Particles ◽

Construction Material ◽

High Water ◽

Production Costs ◽

Fine Tuning ◽

Concrete Technology ◽

Lower Strength ◽

Wide Range ◽

High Level

Self-compacting concretes (SCC) are relatively modern building material that has great potential for using in a wide range of applications. Its origin and development is considered a major breakthrough in concrete technology, especially because of its ease of placement without the need to use external dynamic forces in the form of vibrations. This can significantly affect the resulting properties of concrete as well as working conditions on the building site.To maintain the fresh concrete’s rheological properties and, at the same time, achieve lower final strength, reduced amount of Portland cement needs to be proposed in mixture design. Then, to keep the number of fine particles at high level, it is necessary to use fine grained cement compatible additives which do not chemically participate on hydration process – at least not too much – and thus do not increase the resulting strength.This paper will address the verification of inert additives functionality for the production of lower-strength self-compacting concretes, namely in strength classes C16/20 and C25/30 according to ČSN EN 206. The inert admixture used in this experiment – stone dust from Zelesice quarry – has a relatively high water absorption. Therefore, the particularly crucial part was the fine-tuning of fresh SCC’s rheological properties. The results are clearly pointing to the possibility of lower-strength self-compacting concretes’ production and thus makes it possible to expand the usability portfolio of this type of modern construction material with regard to its lower production costs.

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The way of value of Correlation of genomic DNA microsatellite loci and live weight of Chukchi reindeer

Genetika i razvedenie zhivotnyh ◽

10.31043/2410-2733-2020-3-27-32 ◽

2020 ◽

pp. 27-32

Author(s):

V. Dodokhov ◽

N. Pavlova ◽

T. Rumyantseva ◽

L. Kalashnikova

Keyword(s):

Microsatellite Markers ◽

Agricultural Production ◽

Live Weight ◽

Biodiversity Loss ◽

Tribal Community ◽

High Germination ◽

Wide Range ◽

The Mean ◽

High Level ◽

Dna Microsatellite

The article presents the genetic characteristic of the Chukchi reindeer breed. The object of the study was of the Chukchi reindeer. In recent years, the number of reindeer of the Chukchi breed has declined sharply. Reduced reindeer numbers could lead to biodiversity loss. The Chukchi breed of deer has good meat qualities, has high germination viability and is adapted in adverse tundra conditions of Yakutia. Herding of the Chukchi breed of deer in Yakutia are engaged only in the Nizhnekolymsky district. There are four generic communities and the largest of which is the agricultural production cooperative of nomadic tribal community «Turvaurgin», which was chosen to assess the genetic processes of breed using microsatellite markers: Rt6, BMS1788, Rt 30, Rt1, Rt9, FCB193, Rt7, BMS745, C 143, Rt24, OheQ, C217, C32, NVHRT16, T40, C276. It was found that microsatellite markers have a wide range of alleles and generally have a high informative value for identifying of genetic differences between animals and groups of animal. The number of identified alleles is one of the indicators of the genetic diversity of the population. The total number of detected alleles was 127. The Chukchi breed of deer is characterized by a high level of heterozygosity, and the random crossing system prevails over inbreeding in the population. On average, there were 7.9 alleles (Na) per locus, and the mean number of effective alleles (Ne) was 4.1. The index of fixation averaged 0.001. The polymorphism index (PIC) ranged from 0.217 to 0.946, with an average of 0.695.

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COVID-19 Outbreak Prediction with Machine Learning

10.34055/osf.io/xr4js ◽

2020 ◽

Author(s):

Sina Faizollahzadeh Ardabili ◽

Amir Mosavi ◽

Pedram Ghamisi ◽

Filip Ferdinand ◽

Annamaria R. Varkonyi-Koczy ◽

...

Keyword(s):

Machine Learning ◽

Prediction Models ◽

Fuzzy Inference ◽

Control Measures ◽

Future Research ◽

Complex Nature ◽

Inference System ◽

Wide Range ◽

Standard Models ◽

High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

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CRIMINOLOGICAL FEATURES OF CORRUPTION-RELATED CRIMES IN THE FUEL AND ENERGY COMPLEX

Vestnik Samarskogo iuridicheskogo instituta ◽

10.37523/sui.2020.40.4.003 ◽

2020 ◽

pp. 23-27

Author(s):

Сергей Иванович Вележев ◽

Антон Михайлович Седогин

Keyword(s):

Legal Protection ◽

Criminal Activity ◽

Criminal Cases ◽

Law Enforcement Agencies ◽

Energy Complex ◽

Significant Damage ◽

Study Results ◽

Wide Range ◽

Illegal Activities ◽

High Level

В представленной статье авторами рассматриваются вопросы уголовно-правовой охраны топливно-энергетического комплекса Российской Федерации от преступных проявлений, в том числе от коррупционной противоправной деятельности должностных лиц. Такие действия причиняют значительный ущерб нормальному функционированию предприятий топливно-энергетического комплекса. Авторами приводятся результаты исследования некоторых криминологических характеристик должностных лиц, совершивших преступления коррупционного характера. Дан анализ причин и условий, способствующих совершению вышеуказанных противоправных действий. Определена типовая модель преступника для данной категории преступлений и его характеристики: в первую очередь, это высокий уровень компетентности, специальное образование и т. д. Авторами отмечается высокий уровень латентной преступности в данной отрасли. Предложены некоторые пути профилактики данной категории правонарушений. Исследование проводилось на основе анализа конкретных уголовных дел, возбужденных следственными органами по результатам оперативно-розыскной деятельности правоохранительных органов. In the article the authors consider the issues of criminal and legal protection of the fuel and energy complex of the Russian Federation from criminal activity including corrupt illegal practices of officials. The authors cite the results of some criminological characteristics study of the fuel and energy complex staff committed corruption crimes. As a result of these illegal actions significant damage is caused to the normal functioning of the fuel and energy enterprises. Such officials` actions determine not only a wide range of other illegal activities, but also lead to public outcry and discredit the industry as a whole. The analysis of the reasons and conditions contributing to the above illegal actions commission is given. A typical model of a criminal for a given crime category and its characteristics are determined. First of all it is a high level competence, special education, etc. A high level of latent crime in this industry is shown. The study results are presented on the example of specific criminal cases initiated by the investigating authorities based on the results of the operation detection activities of law enforcement agencies. Some ways of preventing this category of offenses are proposed.

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