Modular Software Research Articles

Towards a Flexible Smart Factory with a Dynamic Resource Orchestration

Amid the current industrial revolution, a total disruption of the existing production lines may seem to be the easiest approach, as the potential possibilities seem limitless when starting from the ground up. On the business side, an adaptation of existing production lines is always a preferred option. In support of adaptation as opposed to disruption, this paper presents a new approach of using production process orchestration in a smart factory, discussed in an industrial case-study example. A proposed smart factory has the Orchestrator component in its core, responsible for complete semantical orchestration of production processes on one hand, and various factory resources on the other hand, in order to produce the desired product. The Orchestrator is a complex, modular, highly scalable, and pluggable software product responsible for automatised planning, scheduling, and execution of the complete production process. According to their offered capabilities, non-smart and smart resources—machines, robots, humans—are simultaneously and dynamically assigned to execute their dedicated production steps.

A Modular Web-Based Software Solution for Mobile Networks Planning, Operation and Optimization

Mobile networks management is increasingly critical due to heavy communications usage by customers and complex due to the multiple technologies and systems deployed. Thus, Mobile Network Operators (MNOs) are constantly looking for better software solutions and tools to help them increase network performance and manage their networks more efficiently. In this paper, we present a modular web-based software solution to tackle problems related to mobile network planning, operation and optimization. The solution is focused on a set of functional requirements carefully chosen to support the network life cycle management, from planning to Operation and Maintenance (OAM) and optimisation stages. Based on a 3-tier modular architecture and implemented using only open-source software, the solution handles multiple data sources (e.g., Drive Test (DT) and Performance Management (PM)) and multiple Radio Access Network (RAN) technologies. MNOs can explore all available data through a flexible and user-friendly web interface, that also includes map-based visualization of the network. Moreover, the solution incorporates a set of recently developed and validated RAN algorithms, supporting tasks of network diagnosis, optimization, and planning. Also, with the purpose of optimizing the network, MNOs can investigate network simulations, using the RAN algorithms, of how the network will behave under certain conditions, and visualize the outcome of those simulations.

DJMol: An open-source modeling platform for computational chemistry and materials science with a Python interpreter.

We present a modular and extendable software suite, DJMol, for performing molecular simulations and it is demonstrated with DFTB+, Siesta, Atomic Simulation Environment, and OpenMD codes. It supports many of the standard features of an integrated development environment and consists of a structure builder and viewer, which could be connected with these electronic structure codes along with a set of data analyzers. This program comprises Java and Python modules and its libraries to carry out a different set of modeling tasks in materials science and chemistry. By adopting a Python interpreter into the software, a range of scriptable Python codes, such as Pymatgen can be incorporated into this programmable modeling platform. DJMol, through its common application programming interface (API), supports multiple modeling codes in the backend and several post-processing tools. It benefits an experienced user by increasing efficiency, while a nonexpert user by easy to use API.

SvaRetro and svaNUMT: modular packages for annotation of retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data

svaRetro and svaNUMT: modular packages for annotation of retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data

Bayesian inference of multimessenger astrophysical data: Methods and applications to gravitational waves

We present ${\tt bajes}$, a parallel and lightweight framework for Bayesian inference of multimessenger transients. ${\tt bajes}$ is a Python modular package with minimal dependencies on external libraries adaptable to the majority of the Bayesian models and to various sampling methods. We describe the general workflow and the parameter estimation pipeline for compact-binary-coalescence gravitational-wave transients. The latter is validated against injections of binary black hole and binary neutron star waveforms, including confidence interval tests that demonstrates the inference is well-calibrated. Binary neutron star postmerger injections are also studied using a network of five detectors made of LIGO, Virgo, KAGRA and Einstein Telescope. Postmerger signals will be detectable for sources at ${\lesssim}80\,$Mpc, with Einstein Telescope contributing over 90\% of the total signal-to-noise ratio. As a full scale application, we re-analyze the GWTC-1 black hole transients using the effective-one-body ${\tt TEOBResumS}$ approximant, and reproduce selected results with other approximants. ${\tt bajes}$ inferences are consistent with previous results; the direct comparison of ${\tt bajes}$ and ${\tt bilby}$ analyses of GW150914 shows a maximum Jensen-Shannon divergence of $5.2{\times}10^{-4}$. GW170817 is re-analyzed using ${\tt TaylorF2}$ with 5.5PN point-mass and 7.5PN tides, ${\tt TEOBResumSPA}$, and ${\tt IMRPhenomPv2\_NRTidal}$ with different cutoff-frequencies of $1024\,$Hz and $2048\,$Hz. We find that the former choice minimizes systematics on the reduced tidal parameter, while a larger amount of tidal information is gained with the latter choice. ${\tt bajes}$ can perform these analyses in about 1~day using 128 CPUs.

An automated low-cost modular hardware and software platform for versatile programmable microfluidic device testing and development

The development of functional microfluidic devices requires multiple iterations of the design, fabrication and testing of an initial concept. Much attention in the literature has been given to improving the design of microdevices, and several rapid-prototyping techniques have been created to fabricate microfluidic structures in the past decade. However, little attention has been given to the testing phase of this iterative process, which is as crucial as the other steps. Testing results “make or break” a concept, and therefore is perhaps the most important phase in design iteration. Conventional approaches to testing microdevices typically require fixed mounts as testbeds, which are usually machined in hard substrates and do not allow for rapid modifications. This, in turn, limits alterations in the design of microfluidic devices, imposing an unnecessary constraint in the iterative development cycle. To alleviate these issues, we present here a new approach to test microfluidic devices by using modules. The modular system contains hardware that can be rapid-prototyped, if needed, speeding up the testing of devices without imposing restrictions on the design of devices. Another innovation presented here is the creation of a new, object-oriented-style language to automate fluidic manipulations in Programmable Microfluidic Arrays (PMAs). This open-source automated computer application, written in Python, requires from the user only the positioning of reservoirs containing reagents, their mixing ratios and the output reservoir, rather than traditional “long-list” or machine-code level programming, representing a significant development in operating these systems. This work decreases the development time and resources required to make functional microfluidic devices, at lower costs, which is an advancement over conventional approaches.

Modular substation intelligent control cabinet temperature control system

When the temperature control system of intelligent control cabinet of modular substation is designed by the current method, the PID controller is not improved, and there are problems such as low temperature prediction accuracy, low temperature tracking accuracy and poor control effect. The design method of temperature control system of intelligent control cabinet of modular substation is proposed. Through FPGA, input circuit, output circuit, man-machine interface, frequency division module five parts constitute the modular substation intelligent control cabinet temperature control system framework, in the temperature control system combined with the predictive function control algorithm to achieve the modular substation intelligent control cabinet temperature control system software system design. The experimental results show that the designed system can control the terminal temperature stably and reduce the temperature fluctuation to a small extent.

Efficient Implementations of Sieving and Enumeration Algorithms for Lattice-Based Cryptography

The security of lattice-based cryptosystems is based on solving hard lattice problems such as the shortest vector problem (SVP) and the closest vector problem (CVP). Various cryptanalysis algorithms such as (Pro)GaussSieve, HashSieve, ENUM, and BKZ have been proposed to solve these hard problems. Several implementations of these algorithms have been developed. On the other hand, the implementations of these algorithms are expected to be efficient in terms of run time and memory space. In this paper, a modular software package/library containing efficient implementations of GaussSieve, ProGaussSieve, HashSieve, and BKZ algorithms is developed. These implementations are considered efficient in terms of run time. While constructing this software library, some modifications to the algorithms are made to increase the performance. Then, the run times of these implementations are compared with the others. According to the experimental results, the proposed GaussSieve, ProGaussSieve, and HashSieve implementations are at least 70%, 75%, and 49% more efficient than previous ones, respectively.

TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance.

Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the advent of IoT, is paving the way for the complete digitization and automation of industrial processes. Maintenance is one of these processes, where the introduction of a predictive approach, as opposed to the traditional techniques, is expected to considerably improve the industry maintenance strategies with gains such as reduced downtime, improved equipment effectiveness, lower maintenance costs, increased return on assets, risk mitigation, and, ultimately, profitable growth. With predictive maintenance, dedicated sensors monitor the critical points of assets. The sensor data then feed into machine learning algorithms that can infer the asset health status and inform operators and decision-makers. With this in mind, in this paper, we present TIP4.0, a platform for predictive maintenance based on a modular software solution for edge computing gateways. TIP4.0 is built around Yocto, which makes it readily available and compliant with Commercial Off-the-Shelf (COTS) or proprietary hardware. TIP4.0 was conceived with an industry mindset with communication interfaces that allow it to serve sensor networks in the shop floor and modular software architecture that allows it to be easily adjusted to new deployment scenarios. To showcase its potential, the TIP4.0 platform was validated over COTS hardware, and we considered a public data-set for the simulation of predictive maintenance scenarios. We used a Convolution Neural Network (CNN) architecture, which provided competitive performance over the state-of-the-art approaches, while being approximately four-times and two-times faster than the uncompressed model inference on the Central Processing Unit (CPU) and Graphical Processing Unit, respectively. These results highlight the capabilities of distributed large-scale edge computing over industrial scenarios.

Introducing GARMI - A Service Robotics Platform to Support the Elderly at Home: Design Philosophy, System Overview and First Results

This letter introduces GARMI, a service robotics platform conceptualized with a focus on assisting elderly at home. GARMI is designed to provide support with household tasks, as an avatar for tactile-enabled communication and as an interface for telemedicine and emergency assistance. Its unique humanoid design features a sensor-equipped multi-modal head designed for natural human-machine communication as well as a whole-body torque-control interface for safe physical human-machine interaction. GARMI's modular software architecture and distinctive whole-body control scheme allows multimodal dynamic coupling. Additionally, every system component can actively produce as well as sense forces and can thus serve as a haptic feedback interface when interacting with its environment and users. Furthermore, GARMI is the first mobile humanoid designed with specialized use-inspired avatar stations: PARTI for dual-arm-based exoskeleton-like remote-control with force-feedback and MUCKI for transparent remote doctor-patient interaction with both audiovisual and safe haptic feedback. The specialized software architecture allows for rapid prototyping and field-testing of new behaviors for telemedicine, multi-modal interaction and autonomous physical and service assistance. Our first results reveal the potential of our use-driven force-based whole-body control mobile humanoid for daily living and telemedicine scenarios in an elderly care research facility.

A Survey on Different Real Time Operating Systems

To minimise development costs and enhance dependability, modern embedded system development is increasingly emphasising on software modularity and reuse. Microcontrollers are extensively employed in embedded applications that have a very specific and specialised job to complete. The embedded applications are always resource constraint which requires efficient utilization of available resources. A Real Time Operating System (RTOS) is frequently used in this context to plan task execution as well as enable intertask communication and synchronisation. This paper provides the survey of different RTOS available in market and their applications. Several open source RTOS such as Free RTOS, VxWorks, SmallRTOS and TinyOS are compared with respect to the scheduling algorithms used.

Synergizing model‐based systems engineering, modularity, and software container concepts to manage obsolescence

AbstractCosts to replace obsolete parts are estimated to exceed $10 billion annually for military expenditures.1 Other industries experience high costs related to obsolete parts as well.2–5 Synergies between Model‐Based Systems Engineering (MBSE) and modular design concepts should be leveraged to reduce those costs early in the design process. To date, obsolescence management, MBSE, and modularity have been studied, advanced, and presented in a mostly disjunct manner. Consequently, work to synergize these areas specifically to mitigate obsolescence impacts is lacking. The research presented herein illuminates that the untapped synergy at the nexus of obsolescence management, MBSE, and modular design can be leveraged to enhance strategic management of obsolescence. Borrowing from the modular software engineering “container” concept6, the MBSE container modeling approach presented provides systems engineers, architects, and designers with a novel method to influence the system design by minimizing the number of system modules affected by obsolescence. By applying this model‐based strategic obsolescence management approach early in the system architecting and design stages, system engineering teams can reduce the associated complexity, lifecycle costs, and risk of obsolete parts replacement.

RapGreen, an interactive software and web package to explore and analyze phylogenetic trees.

RapGreen is a modular software package targeted at scientists handling large datasets for phylogenetic analysis. Its primary function is the graphical visualization and exploration of large trees. In addition, RapGreen offers a tree pattern search function to seek evolutionary scenarios among large collections of phylogenetic trees. Other functionalities include tree reconciliation with a given species tree: the detection of duplication or loss events during evolution and tree rooting. Last but not least, RapGreen features the ability to integrate heterogeneous data while visualizing and otherwise analyzing phylogenetic trees.

Pincho: A Modular Approach to High Quality De Novo Transcriptomics.

Transcriptomic reconstructions without reference (i.e., de novo) are common for data samples derived from non-model biological systems. These assemblies involve massive parallel short read sequence reconstructions from experiments, but they usually employ ad-hoc bioinformatic workflows that exhibit limited standardization and customization. The increasing number of transcriptome assembly software continues to provide little room for standardization which is exacerbated by the lack of studies on modularity that compare the effects of assembler synergy. We developed a customizable management workflow for de novo transcriptomics that includes modular units for short read cleaning, assembly, validation, annotation, and expression analysis by connecting twenty-five individual bioinformatic tools. With our software tool, we were able to compare the assessment scores based on 129 distinct single-, bi- and tri-assembler combinations with diverse k-mer size selections. Our results demonstrate a drastic increase in the quality of transcriptome assemblies with bi- and tri- assembler combinations. We aim for our software to improve de novo transcriptome reconstructions for the ever-growing landscape of RNA-seq data derived from non-model systems. We offer guidance to ensure the most complete transcriptomic reconstructions via the inclusion of modular multi-assembly software controlled from a single master console.

On the development, verification, and validation of a discontinuous Galerkin solver for the Navier-Stokes equations

We present maDG, a newly developed code designed for the efficient parallel implicit solution of the 3D unstructured nodal discontinuous Galerkin discretization of the unsteady compressible Navier-Stokes equations. The code is being developed to provide an efficient, modular, and maintainable software platform for studying algorithmic and modeling issues arising in high-resolution CFD. In this paper we address some issues pertinent to the software architecture and testing implementation used towards the goal of implicit time integration of discontinuous Galerkin (DG) approximations.This effort is largely inspired by the life work of Antony Jameson and by his legendary FLO codes, which for more than four decades have provided a unique platform for the development of CFD methods, and enabled path-breaking advances in aerodynamics. We dedicate this paper to Antony on the occasion of his 85th birthday, with the utmost gratitude for his teaching and his friendship.

Development of Modular Bio-Inspired Autonomous Underwater Vehicle for Close Subsea Asset Inspection

To reduce human risk and maintenance costs, Autonomous Underwater Vehicles (AUVs) are involved in subsea inspections and measurements for a wide range of marine industries such as offshore wind farms and other underwater infrastructure. Most of these inspections may require levels of manoeuvrability similar to what can be achieved by tethered vehicles, called Remotely Operated Vehicles (ROVs). To extend AUV intervention time and perform closer inspection in constrained spaces, AUVs need to be more efficient and flexible by being able to undulate around physical constraints. A biomimetic fish-like AUV known as RoboFish has been designed to mimic propulsion techniques observed in nature to provide high thrust efficiency and agility to navigate its way autonomously around complex underwater structures. Building upon advances in acoustic communications, computer vision, electronics and autonomy technologies, RoboFish aims to provide a solution to such critical inspections. This paper introduces the first RoboFish prototype that comprises cost-effective 3D printed modules joined together with innovative magnetic coupling joints and a modular software framework. Initial testing shows that the preliminary working prototype is functional in terms of water-tightness, propulsion, body control and communication using acoustics, with visual localisation and mapping capability.

Simulation Analysis of Additive Manufacturing of Impeller

An Impeller is the rotating component of a pump; it transfers the energy from the motor to the fluid and accelerates the fluid to build up pressure. Impellers are manufactured using Additive Manufacturing (AM) technology. It is a technology that produces three-dimensional parts layer by layer from a variety of materials such as plastics, polymers and metals. The impeller is usually made up of Stainless Steel 316L, Inconel 718. AM technique used to manufacture impeller is Direct Metal Laser Sintering (DMLS). The main objective of this paper is to conduct simulation analysis of additive manufacturing of an impeller by varying process-parameters such as Power, Wall-thickness and Angle and recommend a suitable material with minimum von-misses stress, minimum displacement and minimum of maximum temperature using Amphyon software. Simulation analysis is performed on two different materials i.e., Stainless Steel 316L and Inconel 718 by varying process parameters such as Power at 200 to 400W, Wall thickness at 0.5 to 0.8mm and Angle at 00 to 60. Amphyon is a modular pre-processing and simulation software for Laser Beam Melting (LBM) processes. The simulation results were analyzed and optimization for Stainless-Steel 316L material impeller was done using one of the MADM methods i.e., Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Later, the results of the two different materials (i.e., Stainless Steel 316L and Inconel 718) were compared. Stainless Steel 316L was found to have minimum von-misses stress, minimum displacement and minimum of maximum temperature at 200W power, 0.5mm wall-thickness and 00 angle. Index Terms: Impeller, Additive Manufacturing, Direct Metal Laser Sintering (DMLS), Amphyon, MADM, TOPSIS.

Разработка модульного программно-аппаратного комплекса управления стендом с моделью космической оранжереи

Space greenhouses (SG) that can be used for enriching the astronauts’ diet are also considered a means of improving the astronauts’ life environment in autonomous crewed expeditions. One of the main requirements for SC is to minimize the specific consumption of the main onboard resources: energy, space, refrigerant, and labor-hours per unit mass of grown product. Experiments on adaptive optimization of irradiation and illumination spectrum were performed and a hardware and software complex (HSC) was developed to control the test-stand with the SG model. The main object of control is an intermittently pressure-sealed chamber with temperature and humidity sensors, as well as an IR gas analyzer. The latter determines the visible photosynthesis of the plants based on the dynamics of CO2 absorption. The sensors and actuators are connected to a Mega 2560 AVR microcontroller connected to a Raspberry Pi 4B single-board computer via a USB-UART converter. The modular software package was created on the basis of the ROS (Robot Operating System) framework, which minimizes the training period for new developers and experiment operators. The first HSC versions were successfully tested on a test-stand with Chinese cabbage to find the trajectory of optimal lighting parameters during the growth process. The HSC made it possible to carry out several replications of a 2-factor experiment to study the drift of the optimal LED lighting modes during a 10 days’ period with daily variation of 2 factors — the current in the red LED circuit and the current in the white LED circuit. Optimal change patterns in the lighting parameters for a test-stand with a space greenhouse model were obtained.

FoodChain-Lab Web: An integrative modular software to visualise and analyse complex global food supply chain networks during foodborne incidents

In times of globalised food and feed trade, powerful integrative software tools are essential to solve foodborne crises quickly and reliably. The FoodChain-Lab web application (FCL Web; https://fcl-portal.bfr.berlin/) is such a tool. FCL Web is free and open-source software which helps to trace back and forward food along complex global supply chains during foodborne disease outbreaks or other food-related events. In the framework of One Health EJP COHESIVE, the efforts of several national and international tracing-related software projects are integrated within FCL Web to provide a modular tracing platform following the One Health approach. FCL Web unifies interactive tracing data visualisation, analysis as well as reporting - and in the future data collection - in one modular tracing platform (Fig. 1). The interactive analysis module was developed in a project with EFSA and offers automated visualisation of supply chains based on the needs of the user. A data table displays key information on involved food business operators and food items and includes comprehensive filter functions to analyse the information given in the table. The analysis module also helps to run simulations on hypothetical cross contamination or geographic clustering events during outbreaks via a scoring algorithm for deliveries and food business operators. A pilot version of a reporting module was integrated in FCL Web as well to display tracing, sample and case information in a format suitable for publishing tracing results in outbreak reports. A web-based tracing data collection mask offering a guided and structured data assessment with access to curated data was developed in a national project and will be integrated in FCL Web soon. Its multi-language design allows for potential European-wide use. In the future, more modules, e.g. to analyse genome sequencing data in the context of tracing are planned for FCL Web. With its features and its integrative approach, FCL Web blends seamlessly into a list of crucial tracing tool projects in Europe. In the future, these tools will be strongly interconnected to serve several tracing purposes on the local, national or European level. Hence, there is a need to improve interoperability of the tools e.g. via a universal data exchange format.

The abTEM code: transmission electron microscopy from first principles.

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document. This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fastimplementation of thePRISM algorithm for a decahedral 20000-atom gold nanoparticle.