Open-source Code Library Research Articles

Application of a Comprehensive Treatment Planning Test for Credentialing Intensity-Modulated Radiotherapy and RapidArc in a TrueBeam Linear Accelerator Setup.

An extended version of task group report (TG)-119 dosimetric tests was introduced and tested on the TrueBeam linear accelerator setup. Treatment plan results and quality assurance (QA) results of RapidArc (RA) and intensity-modulated radiotherapy (IMRT) were compared to understand the limitation and efficacy of the RA and IMRT system of the linear accelerator. Test structure sets were drawn on OCTAVIUS four-dimensional (4D) phantom computed tomography scan data for this study. We generated treatment plans based on the specified goal in the Eclipse™ treatment planning system using RA and IMRT in the study phantom. We used the same planning objectives for RA and IMRT techniques. Planar dose verification was performed using electronic portal imaging device and OCTAVIUS 4D phantom. The treatment log file was further analyzed using Pylinac (V2.4.0 (Open Source Code library available on Github, runs under Python programming language)) to compare the dosimetric outcome of RA and IMRT. Dose to the planning target volume (PTV) 1-5 and organ at risk (OAR) were analyzed in this study for the efficiency comparison of RA and IMRT. The primary objective was accomplished by adhering to the dose constraints associated with PTV 2 and the OAR. RA and IMRT also met the secondary objective. The tertiary goal of dose delivery to PTV 4 was met with RA but not IMRT. This study can be utilized to compare different institutions' planning and patient-specific QA (PSQA) procedures. The findings of this study were in line with the published works of the literature. A multi-institutional planning and delivery accuracy audit can be built using this structure and set of planning objectives having similar PSQA phantom. The TG-119 report incorporated test challenges that were combined in a single study set and a single plan. This reduces the complexity of performing the original TG-119 tests, whereas keeping the challenges as introduced in the TG-119 report. This study's planning and dosimetric results could be further utilized for dosimetry audit with any institute having a linear accelerator and OCTAVIUS 4D phantom for PSQA.

Representation Learning in Multi-view Clustering: A Literature Review

Multi-view clustering (MVC) has attracted more and more attention in the recent few years by making full use of complementary and consensus information between multiple views to cluster objects into different partitions. Although there have been two existing works for MVC survey, neither of them jointly takes the recent popular deep learning-based methods into consideration. Therefore, in this paper, we conduct a comprehensive survey of MVC from the perspective of representation learning. It covers a quantity of multi-view clustering methods including the deep learning-based models, providing a novel taxonomy of the MVC algorithms. Furthermore, the representation learning-based MVC methods can be mainly divided into two categories, i.e., shallow representation learning-based MVC and deep representation learning-based MVC, where the deep learning-based models are capable of handling more complex data structure as well as showing better expression. In the shallow category, according to the means of representation learning, we further split it into two groups, i.e., multi-view graph clustering and multi-view subspace clustering. To be more comprehensive, basic research materials of MVC are provided for readers, containing introductions of the commonly used multi-view datasets with the download link and the open source code library. In the end, some open problems are pointed out for further investigation and development.

A Survey on Blockchain for Information Systems Management and Security

Blockchain technologies have grown in prominence in recent years, with many experts citing the potential applications of the technology in regard to different aspects of any industry, market, agency, or governmental organizations. In the brief history of blockchain, an incredible number of achievements have been made regarding how blockchain can be utilized and the impacts it might have on several industries. The sheer number and complexity of these aspects can make it difficult to address blockchain potentials and complexities, especially when trying to address its purpose and fitness for a specific task. In this survey, we provide a comprehensive review of applying blockchain as a service for applications within today’s information systems. The survey gives the reader a deeper perspective on how blockchain helps to secure and manage today information systems. The survey contains a comprehensive reporting on different instances of blockchain studies and applications proposed by the research community and their respective impacts on blockchain and its use across other applications or scenarios. Some of the most important findings this survey highlights include the fact that blockchain’s structure and modern cloud- and edge-computing paradigms are crucial in enabling a widespread adaption and development of blockchain technologies for new players in today unprecedented vibrant global market. Ensuring that blockchain is widely available through public and open-source code libraries and tools will help to ensure that the full potential of the technology is reached and that further developments can be made concerning the long-term goals of blockchain enthusiasts.

ROBUSTNESS IMPROVEMENT USING OPEN SOURCE CODE LIBRARIES

AbstractComputer tools are commonly used to assess designs. We develop a toolchain using open source code libraries in Python to provide an open source, interactive robust design improvement toolchain. A reference folder contains a script that reads an input parameter value file and runs the simulation. The toolchain executes uncertainty quantification steps by replicating the reference folder. This is repeated for design points, and mean and sigma graphs generated versus each design variable. This fits within a workflow of defining variation modes, design variables, and toolchain execution.

The Geodynamic World Builder: a solution for complex initial conditions in numerical modeling

Abstract. The Geodynamic World Builder is an open-source code library intended to set up initial conditions for computational geodynamic models in both Cartesian and spherical geometries. The inputs for the JavaScript Object Notation (JSON)-style parameter file are not mathematical but rather a structured nested list describing tectonic features, e.g., a continental, an oceanic or a subducting plate. Each of these tectonic features can be assigned a specific temperature profile (e.g., plate model) or composition label (e.g., uniform). For each point in space, the Geodynamic World Builder can return the composition and/or temperature. It is written in C++ but can be used in almost any language through its C and Fortran wrappers. Various examples of 2-D and 3-D subduction settings are presented. The Geodynamic World Builder comes with an extensive online user manual.

Using Open Source Code Libraries for Robust Design Analysis

AbstractThe design of systems today often involves computer simulation to assess performance and design margins. Understanding how variability erases design margin is important to assure adequacy of margins, especially in optimization efforts. In this paper, we develop a toolchain using open source code libraries in Python, and encapsulate it in Jupyter notebooks, to provide an open source, interactive uncertainty quantification and sensitivity analysis toolchain. This works generally with simulation tools, where a reference folder is created containing a script that reads an input file of parameter values and runs the simulation. With that easily created, the toolchain executes the necessary uncertainty quantification steps with replicates of that reference folder. This approach fits within a broader workflow outlined that defines the variation modes to study, maps to simulation inputs, and screens the variables for sensitivity before conducting an uncertainty quantification. An example is shown in the simulation analysis of a Stirling engine.

Simulation on tsunami-like solitary wave run-up around a conical island using a modified mass source method

Predicting the maximum run-up height and inundated area caused by tsunami events has been a hotly debated topic recently. Nevertheless, the wave height-to-depth ratios (nonlinearity) adapted previously tended to be conservative, considering the fact that a tsunami wave is an extreme wave condition with large wave height. In the present study, a mass source wave-generating approach for highly nonlinear waves is presented using our in-house solver, DUT-FOAM, which is a hydrodynamic solver developed using the open source code library OpenFOAM. By fully considering the mass output from the source region, a more reasonable mass source function has been obtained to compensate for the inadequacy of original method in simulating highly nonlinear waves. A newly designed numerical wave tank is performed for different nonlinearities. Numerical simulations of tsunami wave propagating to a conical island are carried. Fairly good agreements are obtained from the qualitative and quantitative comparisons between numerical results (Liu, Cho, Briggs, Kanoglu, & Synolakis, 1995) and laboratory data (Briggs, Synolakis, Harkins, & Green, 1995) regarding run-up maps around the island. The comparison reveals that present model offers a fast and accurate way to simulate highly nonlinear waves and is potentially useful and efficient for forecasting the run-up heights.

Using TensorFlow-based Neural Network to estimate GNSS single frequency ionospheric delay (IONONet)

In the last 20 years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2 m.

Noninvasive numerical simulation of coronary fractional flow reserve based on lattice Boltzmann method

In order to investigate the application of lattice Boltzmann method (LBM) in the numerical simulation of computed tomography angiography-derived fractional flow reserve (FFR CT), an idealized narrowed tube model and two coronary stenosis arterymodels are studied. Based on the open source code library (Palabos), the relative algorithm program in the development environment (Codeblocks) was improved. Through comparing and analyzing the results of FFR CT which is simulated by LBM and finite element analysis software ANSYS, and the feasibility of the numerical simulation of FFR CT by LBM was verified . The results show that the relative error between the results of LBM and finite element analysis software ANSYS is about 1%, which vertifies the feasibility of simulating the coronary FFR CT by LBM. The simulation of this study provides technical support for developing future FFR CT application software, and lays the foundation for the calculation of clinical FFR CT.

Open source and the Internet of Things

The Internet of Things (IoT) is gaining a reputation for insecurity. Researchers have revealed dangerous flaws in everything from baby monitors to power stations. And much of the problem stems from an attitude of ‘innovate now, secure later’. In this interview with Tim Mackey, technical evangelist at Black Duck Software by Synopsys, we look at what the IoT encompasses, why so much of it appears to be flaky or downright dangerous and how the unquestioning and promiscuous use of readymade solutions, including open source code libraries, can have serious consequences. The Internet of Things (IoT) is gaining a reputation for insecurity. Researchers have revealed dangerous flaws in everything from baby monitors to power stations. Much of the problem stems from an attitude of ‘innovate now, secure later’. In this interview with Tim Mackey of Black Duck Software, we look at what the IoT encompasses, why so much of it appears to be flaky or downright dangerous and how the promiscuous use of readymade solutions, including open source code libraries, can have serious consequences.

A Comparison of Simplified Two-dimensional Flow Models Exemplified by Water Flow in a Cavern

Abstract The paper shows the results of a comparison of simplified models describing a two-dimensional water flow in the example of a water flow through a straight channel sector with a cavern. The following models were tested: the two-dimensional potential flow model, the Stokes model and the Navier-Stokes model. In order to solve the first two, the boundary element method was employed, whereas to solve the Navier-Stokes equations, the open-source code library OpenFOAM was applied. The results of numerical solutions were compared with the results of measurements carried out on a test stand in a hydraulic laboratory. The measurements were taken with an ADV probe (Acoustic Doppler Velocimeter). Finally, differences between the results obtained from the mathematical models and the results of laboratory measurements were analysed.

Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review

Despite its short history, the use of Riemannian geometry in brain-computer interface (BCI) decoding is currently attracting increasing attention, due to accumulating documentation of its simplicity, accuracy, robustness and transfer learning capabilities, including the winning score obtained in five recent international predictive modeling BCI data competitions. The Riemannian framework is sharp from a mathematical perspective, yet in practice it is simple, both algorithmically and computationally. This allows the conception of online decoding machines suiting real-world operation in adverse conditions. We provide here a review on the use of Riemannian geometry for BCI and a primer on the classification frameworks based on it. While the theoretical research on Riemannian geometry is technical, our aim here is to show the appeal of the framework on an intuitive geometrical ground. In particular, we provide a rationale for its robustness and transfer learning capabilities and we elucidate the link between a simple Riemannian classifier and a state-of-the-art spatial filtering approach. We conclude by reporting details on the construction of data points to be manipulated in the Riemannian framework in the context of BCI and by providing links to available open-source Matlab and Python code libraries for designing BCI decoders.

LibCoopt: A library for combinatorial optimization on partial permutation matrices

LibCoopt is an open-source matlab code library which provides a general and convenient tool to approximately solve the combinatorial optimization problems on the set of partial permutation matrices, which are frequently encountered in computer vision, bioinformatics, social analysis, etc. To use the library, the user needs only to give the objective function and its gradient function associated with the problem. Two typical problems, the subgraph matching problem and the quadratic assignment problem, are employed to illustrate how to use the library and also its flexibility on different types of problems.

Hydrodynamical aspects of the floating zone silicon crystal growth process

3D numerical modeling of dopant transport in the melt is carried out for the 100mm floating zone silicon single crystal growth process. The axis-symmetric shape of the molten zone is calculated with the program FZone considering the coil and the high frequency (HF) electromagnetic (EM) field in 3D. Time dependent melt flow, temperature and dopant concentration fields are modeled using a specialized solver based on the open source code library OpenFOAM®. The influence of the Marangoni coefficient in the boundary conditions on the melt velocity field is analyzed. The obtained shapes of the crystallization interface and resistivity profiles in the grown crystal are compared with experimental results. Differences between axis-symmetric and non-symmetric models are analyzed.

Flow modelling with relevance to vertical gradient freeze crystal growth under the influence of a travelling magnetic field

Results on the experimental and numerical modelling of the melt flow typically observed in vertical gradient freeze (VGF) crystal growth with a travelling magnetic field (TMF) are presented. Particular attention is paid on the transition from a laminar to a time-dependent flow, which represents a crucial problem in VGF growth. Low-temperature model experiments at around 80°C were performed using a GaInSn melt in a resistance furnace with concentric, separately adjustable heating zones. The TMF was created by an external coil system, and the flow velocity was measured by means of the ultrasonic Doppler velocimetry (UDV). The melt flow was simulated numerically using a finite volume code based on the open source code library OpenFOAM. As a criterion for the stability of the flow the turbulent kinetic energy was calculated under the influence of the TMF and thermal buoyancy. The results obtained are compared to isothermal TMF flow modelling at ambient temperature. The stability limit of the melt flow is found to be significantly influenced by the mutual interaction of buoyant and TMF-driven flows. Both experimental and numerical results show the stabilizing effect of natural, VGF-type buoyancy on the TMF-induced flow.

Applicability of LES turbulence modeling for CZ silicon crystal growth systems with traveling magnetic field

To examine the applicability of LES turbulence modeling for CZ silicon crystal growth systems with traveling magnetic fields, LES calculations with Smagorinsky–Lilly turbulence model and van Driest damping at the solid walls are carried out. The program package for the calculations was developed on the basis of the open-source code library OpenFOAM ® . A previously published laboratory model with low temperature melt InGaSn, a 20” crucible, and process parameters corresponding to industrial Czochralski silicon systems is considered. Flow regimes with two crystal and crucible rotation rates and with different strengths of the traveling magnetic field “down” are analyzed. The calculated distributions of averaged temperature and standard temperature deviations are compared with measured ones in the laboratory system, and a relatively good agreement between them is shown. The influence of chosen time steps and grid sizes is analyzed by comparing Fourier spectra of temperature time-autocorrelation functions and temperature spatial distributions, and it is shown that the used moderate meshes of few hundred thousand cells can be applied for practical calculations.

Amorphous track models: A numerical comparison study

We present an open-source code library for amorphous track modelling which is suppose to faciliate the application and numerical comparability as well as serve as a frame-work for the implementation of new models. We show an example of using the library indicating the choice of submodels has a significant impact on the modelling outcome.