Open Source Software Components Research Articles

A Guide to Measuring Heart and Respiratory Rates Based on Off-the-Shelf Photoplethysmographic Hardware and Open-Source Software.

The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among the various techniques available, photoplethysmography stands out as particularly promising for assessing vital signs such as heart rate, respiratory rate, oxygen saturation, and blood pressure. Despite the efficacy of this method, many commercially available wearables, bearing Conformité Européenne marks and the approval of the Food and Drug Administration, are often integrated within proprietary, closed data ecosystems and are very expensive. In an effort to democratize access to affordable wearable devices, our research endeavored to develop an open-source photoplethysmographic sensor utilizing off-the-shelf hardware and open-source software components. The primary aim of this investigation was to ascertain whether the combination of off-the-shelf hardware components and open-source software yielded vital-sign measurements (specifically heart rate and respiratory rate) comparable to those obtained from more expensive, commercially endorsed medical devices. Conducted as a prospective, single-center study, the research involved the assessment of fifteen participants for three minutes in four distinct positions, supine, seated, standing, and walking in place. The sensor consisted of four PulseSensors measuring photoplethysmographic signals with green light in reflection mode. Subsequent signal processing utilized various open-source Python packages. The heart rate assessment involved the comparison of three distinct methodologies, while the respiratory rate analysis entailed the evaluation of fifteen different algorithmic combinations. For one-minute average heart rates' determination, the Neurokit process pipeline achieved the best results in a seated position with a Spearman's coefficient of 0.9 and a mean difference of 0.59 BPM. For the respiratory rate, the combined utilization of Neurokit and Charlton algorithms yielded the most favorable outcomes with a Spearman's coefficient of 0.82 and a mean difference of 1.90 BrPM. This research found that off-the-shelf components are able to produce comparable results for heart and respiratory rates to those of commercial and approved medical wearables.

NMRduino: A modular, open-source, low-field magnetic resonance platform

The NMRduino is a compact, cost-effective, sub-MHz NMR spectrometer that utilizes readily available open-source hardware and software components. One of its aims is to simplify the processes of instrument setup and data acquisition control to make experimental NMR spectroscopy accessible to a broader audience. In this introductory paper, the key features and potential applications of NMRduino are described to highlight its versatility both for research and education.

Implementing Internet of Things Service Platforms with Network Function Virtualization Serverless Technologies

The need for adaptivity and scalability in telecommunication systems has led to the introduction of a software-based approach to networking, in which network functions are virtualized and implemented in software modules, based on network function virtualization (NFV) technologies. The growing demand for low latency, efficiency, flexibility and security has placed some limitations on the adoption of these technologies, due to some problems of traditional virtualization solutions. However, the introduction of lightweight virtualization approaches is paving the way for new and better infrastructures for implementing network functions. This article discusses these new virtualization solutions and shows a proposal, based on serverless computing, that uses them to implement container-based virtualized network functions for the delivery of advanced Internet of Things (IoT) services. It includes open source software components to implement both the virtualization layer, implemented through Firecracker, and the runtime environment, based on Kata containers. A set of experiments shows that the proposed approach is fast, in order to boost new network functions, and more efficient than some baseline solutions, with minimal resource footprint. Therefore, it is an excellent candidate to implement NFV functions in the edge deployment of serverless services for the IoT.

Smart Melon Farm System: Fertilizer IoT Solution

Embedded systems are increasingly being employed for a wide range of applications. Small and large enterprises can benefit from sensor networks and Internet of Things technologies. Farmers, particularly the next generation of farmers, are tremendously interested in the smart farm system. This is due to Thailand’s favorable geography, and young farmers are becoming more technologically literate. However, smart farm systems on the market are still too expensive and don’t meet small farms’ needs. Consequently, the study proposed a low-cost irrigation and fertilizer system for high-quality melon farms in Chiang Rai, Thailand. The system can properly carry out irrigation and fertilization operations on the melon farm, which require specific attention at various stages of production. As a result, the technique reduces human work while simultaneously supplying adequate water and nutrients to the entire plant. Moreover, farmers with Internet access can manually monitor or supervise the operation at any time, from any location, and on any device. The developed system may gather information from sensors and operational procedures for further analysis in order to increase output and reduce waste. The system is affordable since it was constructed primarily using open-source software and low-cost embedded components with an ergonomic architecture. The results of the comparison show that the automatic method outperforms the human approach in terms of quality and production yield.

Enabling Real-Time Remote Monitoring of Ships by Lossless Protocol Transformations

This paper uses data processing techniques to reduce the required transmission bandwidth in ship-to-shore communications. The proposed framework (ONline Efficient Sources Transmission Optimizer -) leverages state-of-the-art technologies and novel algorithms to automatically optimize transmissions under structural (e.g., available bandwidth, fixed packet overhead) and user-defined (e.g., maximum latency) constraints. In addition, authenticates and encrypts the communication between the ship and the shore via mainstream free and open-source software components. Initially, we present the abstract mathematical formulation of the problem, with its assumptions, goal function, constraints, and significant quantities. Then, we introduce the architecture of a system capable of continuously estimating the compressibility, processing and transmission time of streaming data. Such estimations allow to calculate and apply optimal parameters for achieving the best compression ratio. Lastly, using a prototypical implementation, we evaluate the system performance with a Class B ship simulator on two realistic use cases. Our experiments show an excellent compression ratio with maritime protocols (more than 40:1) and a limited latency impact, demonstrating the approach’s viability.

Analysis of software bill of materials tools

Modern software development has gradually become more complex, leveraging available open-source software and third-party components. This practice has raised questions about the provenance, licensing, versioning and compliance of reused code and its dependencies. Furthermore, it is particularly important to review such code fragments and third-party components for known vulnerabilities before they are included in a software product. A Software Bill of Materials (SBoM) is a mechanism to achieve such an analysis, providing transparency and visibility into a software product to both the software developer and its respective consumer. SBoM lists information and details about all the elements constituting a piece of software and can, therefore, be used to evaluate associated security risk. While the concept of SBoM is growing in popularity, it is still fairly new to many organisations, causing them to potentially struggle with producing and processing SBoM and limiting their widespread adoption. In this work, we delve into the area of SBoM and present state-of-the-art SBoM tools, creating a framework for analysis and categorising them based on a diverse set of features and functionalities. We are the first to provide a detailed analysis of 83 open-source SBoM tools along with a perspective on how potential SBoM users can select a tool based on their specific requirements. Our work aims to help promote understanding of this domain, thereby encouraging and furthering its overall adoption. We additionally seek to pave a path for future work in this area by providing recommendations to tool developers and users, researchers and standardising organisations.

Finite Element Analysis of Microwave Tumor Ablation Based on Open-Source Software Components

Microwave ablation is a procedure for treating various types of cancers during which a small needle-like probe is inserted inside the tumor, which delivers microwave energy, causes tissue heating, and effectively produces necrosis of the tumor tissue. Mathematical models of microwave ablation involve the modeling of multiple physical phenomena that occur during the procedure, including electromagnetic wave propagation, heat transfer, and tissue damage. In this study, a complete model of a microwave ablation procedure based on open-source software components is presented. First, the comprehensive procedure of mesh creation for the complete geometric arrangement of the microwave ablation, including a multi-slot coaxial antenna, a real liver tumor taken from the database, and the surrounding liver tissue, is described. It is demonstrated that utilizing smart meshing procedures significantly reduces the usage of computational resources and simulation time. An accurate custom explicit Euler time loop was designed to obtain temperature values and estimate tissue necrosis across the computational domain during the time of microwave ablation. The simulation results obtained by solving the electromagnetic field using the finite element method in the frequency domain are presented and analyzed. The simulation was performed for a microwave frequency of 2.45 GHz, and the volumetric distribution of temperature and estimation of cell damage over 600 s are presented.

FAIRness through automation: development of an automated medical data integration infrastructure for FAIR health data in a maximum care university hospital

BackgroundSecondary use of routine medical data is key to large-scale clinical and health services research. In a maximum care hospital, the volume of data generated exceeds the limits of big data on a daily basis. This so-called “real world data” are essential to complement knowledge and results from clinical trials. Furthermore, big data may help in establishing precision medicine. However, manual data extraction and annotation workflows to transfer routine data into research data would be complex and inefficient. Generally, best practices for managing research data focus on data output rather than the entire data journey from primary sources to analysis. To eventually make routinely collected data usable and available for research, many hurdles have to be overcome. In this work, we present the implementation of an automated framework for timely processing of clinical care data including free texts and genetic data (non-structured data) and centralized storage as Findable, Accessible, Interoperable, Reusable (FAIR) research data in a maximum care university hospital.MethodsWe identify data processing workflows necessary to operate a medical research data service unit in a maximum care hospital. We decompose structurally equal tasks into elementary sub-processes and propose a framework for general data processing. We base our processes on open-source software-components and, where necessary, custom-built generic tools.ResultsWe demonstrate the application of our proposed framework in practice by describing its use in our Medical Data Integration Center (MeDIC). Our microservices-based and fully open-source data processing automation framework incorporates a complete recording of data management and manipulation activities. The prototype implementation also includes a metadata schema for data provenance and a process validation concept. All requirements of a MeDIC are orchestrated within the proposed framework: Data input from many heterogeneous sources, pseudonymization and harmonization, integration in a data warehouse and finally possibilities for extraction or aggregation of data for research purposes according to data protection requirements.ConclusionThough the framework is not a panacea for bringing routine-based research data into compliance with FAIR principles, it provides a much-needed possibility to process data in a fully automated, traceable, and reproducible manner.

Side channel attack performance of correlation power analysis method in noise

This article explores the use of artificial noise to defend against power analysis and power analysis-based side-channel attacks on AES encryption. The study covers both hardware and open-source software components for performing power analysis and provides an analysis of attack performance. It also explains how security measures against side-channel attacks can be implemented without disrupting system operation.

РАЗРАБОТКА АЛГОРИТМОВ ДЛЯ ВЫБОРКИ ДАННЫХ В КОМПОНЕНТАХ ОБЛАЧНОЙ ИНФРАСТРУКТУРЫ

The digital transformation of companies leads to the transfer of many technological and business processes to the cloud, which leads to new risks of confidential information presented in different data formats in the cloud infrastructure, as well as the complexity and heterogeneity of the cloud infrastructure. Cloud infocommunication systems built upon open-source software components expose variabilities in data formats and structures. Such data formats and structures may be convenient and reasonable when developing cloud components, although working with it during operation and maintenance is accompanied with the problem of a mismatch between the varieties and with the lack of special tools to query among the multiple data formats. In the article such data formats as YAML, JSON and XML are considered and thus an opportunity of its transformation into a single format is taken as a hypothesis. Considering analysis results of original data samples taken from OpenStack components three typical data structures are proposed. The other hypothesis is about the opportunity to join data taken from multiple sources. In order to verify assumptions, the algorithms for data transformation into a tabular format are developed. The quickness of transformations is verified on a large sample and obtained results are acceptable for usage while operating and maintaining cloud infocommunication systems. After applying the proposed algorithms to the original data samples an SQL query and a way to query on multiple data sources are proposed. The results of research may have an application for the cloud infrastructure availability solutions when working with multiple data formats.

Development of an Open-Source Testbed Based on the Modbus Protocol for Cybersecurity Analysis of Nuclear Power Plants

The possibility of cyber-attacks against critical infrastructure, and in particular nuclear power plants, has prompted several efforts by academia. Many of these works aim to capture the vulnerabilities of the industrial control systems used in these plants through computer simulations and hardware in the loop configurations. However, general results in this area are limited by the cost and diversity of existing commercial equipment and protocols, as well as by the inherent complexity of the nuclear plants. In this context, this work introduces a testbed for the study of cyber-attacks against a realistic simulation of a nuclear power plant. Our approach consists in surveying issues regarding realistic simulations of nuclear power plants and to design and experimentally validate a software testbed for the controlled analysis of cyberattacks against the simulated nuclear plant. The proposal integrates a simulated Modbus/TCP network environment containing basic industrial control elements implemented with open-source software components. We validate the proposed testbed architecture by performing and analyzing a representative cyberattack in the developed environment, thus showing the principles for the analysis of other possible cybernetic attacks.

A Persistent Sea-Going Platform for Robotic Fish Telemetry Using a Wave-Propelled USV: Technical Solution and Proof-of-Concept

Over the last few decades, acoustic fish telemetry has developed into a viable approach for remote monitoring of fish behaviour in the marine environment. Simultaneously, unmanned surface and underwater vehicles have found extensive use as scalable, persistent and cost-effective platforms for ocean observation. Equipping such robotic vehicles with fish telemetry receivers constitutes an emerging approach with the potential to significantly push the current operational limits of fish movement studies at sea. Here, we present an energy-autonomous robotic fish telemetry platform realised through the integration of a real-time acoustic receiver into an ocean-going wave- and solar-powered unmanned surface vehicle. The vehicle frame and energy harvesting solutions are based on the commercially available AutoNaut USV, while the vehicle’s control and communication systems were developed using open-source software and standard hardware components. The open architecture permitted deep integration of the acoustic receiver as a system-level payload making fish detections and other sensor data available in real-time to the vehicle’s onboard control system. The vehicle is thus prepared with local situational awareness to support autonomous control during vehicle-fish encounters, as well as conventional interfaces for remote piloting and data management through long-range wireless communication links and the Internet. The vehicle concept was investigated theoretically and experimentally in an acoustic range test and a full-scale sea trial. When driven passively by waves, tag detection performance was comparable to that of traditional moored receivers, while activation of the auxiliary electric thruster caused a reduction in detection radius of more than 50%, confirming wave-power as the ideal mode of propulsion. Finally, by deploying the AutoNaut over a period of several days at the outskirts of a Norwegian fjord during the seaward migration of Atlantic salmon post-smolts, we demonstrated that the vehicle was able to detect an acoustically tagged post-smolt into the open ocean beyond the reach of the fjord’s stationary receiver grid, while using only wave- and solar energy harvesting to power its operation. The ability to observe small individual fish in the ocean environment using an energy-autonomous robotic vehicle creates novel and unprecedented opportunities for scientific inquiry in fish behaviour and movement ecology studies at sea.

OSSARA: Abandonment Risk Assessment for Embedded Open Source Components

Systems with unmaintained embedded open source software (OSS) components are vulnerable to severe risks. This article introduces the OSS Abandonment Risk Assessment model to help companies avoid potentially dire consequences.

Hydrological Web Services for Operational Flood Risk Monitoring and Forecasting at Local Scale in Niger

Emerging hydrological services provide stakeholders and political authorities with useful and reliable information to support the decision-making process and develop flood risk management strategies. Most of these services adopt the paradigm of open data and standard web services, paving the way to increase distributed hydrometeorological services’ interoperability. Moreover, sharing of data, models, information, and the use of open-source software, greatly contributes to expanding the knowledge on flood risk and to increasing flood preparedness. Nevertheless, services’ interoperability and open data are not common in local systems implemented in developing countries. This paper presents the web platform and related services developed for the Local Flood Early Warning System of the Sirba River in Niger (SLAPIS) to tailor hydroclimatic information to the user’s needs, both in content and format. Building upon open-source software components and interoperable web services, we created a software framework covering data capture and storage, data flow management procedures from several data providers, real-time web publication, and service-based information dissemination. The geospatial infrastructure and web services respond to the actual and local decision-making context to improve the usability and usefulness of information derived from hydrometeorological forecasts, hydraulic models, and real-time observations. This paper presents also the results of the three years of operational campaigns for flood early warning on the Sirba River in Niger. Semiautomatic flood warnings tailored and provided to end users bridge the gap between available technology and local users’ needs for adaptation, mitigation, and flood risk management, and make progress toward the sustainable development goals.

Design of a scanning acoustic and photoacoustic microscopy system using open-source hardware and software components

We have designed and started construction of an instrument that will be able to operate as both a scanning acoustic microscope and photoacoustic microscope. To keep costs down, we are using open-source hardware and software components wherever possible. The system is designed to scan specimens that are approximately 2 cm × 2 cm in lateral dimensions with lateral steps of 1 micron or less. When operating as a scanning acoustic microscope, the specimen will be water-coupled to a high-frequency ultrasound transducer operating in pulse-echo mode. When operating as a photoacoustic microscope, short light pulses infrared laser diode located under the specimen will generate ultrasound pulses thermoelastically, which will then be received by a confocal high-frequency transducer. In both cases, the specimen will be raster-scanned under the transducer by a moving stage. The mechanical scanning system was designed and built using a spring-loaded microscope stage, micrometers, stepper motors, a shield board used for 3D printers, an Arduino Mega microcontroller, and a Raspberry Pi 4 microcomputer. A graphical user interface has been written in Python using Tkinter to send the motion control commands to the stage. Future work will include incorporation of the laser and transducer control systems.

Exploring factors and metrics to select open source software components for integration: An empirical study

Context:Open Source Software (OSS) is nowadays used and integrated in most of the commercial products. However, the selection of OSS projects for integration is not a simple process, mainly due to a of lack of clear selection models and lack of information from the OSS portals. Objective:We investigate the factors and metrics that practitioners currently consider when selecting OSS. We also investigate the source of information and portals that can be used to assess the factors, as well as the possibility to automatically extract such information with APIs. Method:We elicited the factors and the metrics adopted to assess and compare OSS performing a survey among 23 experienced developers who often integrate OSS in the software they develop. Moreover, we investigated the APIs of the portals adopted to assess OSS extracting information for the most starred 100K projects in GitHub. Result:We identified a set consisting of 8 main factors and 74 sub-factors, together with 170 related metrics that companies can use to select OSS to be integrated in their software projects. Unexpectedly, only a small part of the factors can be evaluated automatically, and out of 170 metrics, only 40 are available, of which only 22 returned information for all the 100K projects. Therefore, we recommend project maintainers and project repositories to pay attention to provide information for the project they are hosting, so as to increase the likelihood of being adopted. Conclusion:OSS selection can be partially automated, by extracting the information needed for the selection from portal APIs. OSS producers can benefit from our results by checking if they are providing all the information commonly required by potential adopters. Developers can benefit from our results, using the list of factors we selected as a checklist during the selection of OSS, or using the APIs we developed to automatically extract the data from OSS projects.

A High-Performance Gamma Spectrometer for Unmanned Systems Based on Off-the-Shelf Components

Since the Fukushima Daiichi Nuclear Power Plant accident in March 2011, the technology available for unmanned aerial vehicles (UAVs) for radiation monitoring has improved greatly. Remote access to radiation-contaminated areas not only eliminates unnecessary exposure of civilians or military personnel, but also allows workers to explore inaccessible places. Hazardous levels of radioactive contamination can be expected as a result of accidents in the nuclear power industry or as a result of the intentional release of radioactive materials for terrorist purposes (dirty bombs, building contamination, etc.). The possibility to detect, identify, and characterize radiation and nuclear material using mobile and remote sensing platforms is a common requirement in the radiation sensing community. The technology has applications in homeland security and law enforcement, customs and border protection, nuclear power plant safety and security, nuclear waste monitoring, environmental recovery, and the military. In this work, the authors have developed, implemented, and characterized a gamma-ray detection and spectroscopy system capable of operating on a UAV. The system was mainly developed using open-source software and affordable hardware components to reduce development and maintenance costs and provide satisfactory performance as a detection instrument. The designed platform can be used to perform mapping or localization tasks to improve the risk assessment process for first responders during the management of radiological and nuclear incidents. First, the design process of the system is described; the result of the characterization of the platform is then presented together with the use of the prototype installed on a UAV in an exercise simulating a radiological and nuclear contamination scenario.

Considerations and challenges for the adoption of open source components in software-intensive businesses

Component-Based Software Development is a conventional way of working for software-intensive businesses and Open Source Software (OSS) components are frequently considered by businesses for adoption and inclusion in software products. Previous research has found a variety of practices used to support the adoption of OSS components, including formally specified processes and less formal, developer-led approaches, and that the practices used continue to develop. Evolutionary pressures identified include the proliferation of available OSS components and increases in the pace of software development as businesses move towards continuous integration and delivery. We investigate work practices used in six software-intensive businesses in the primary and secondary software sectors to understand current approaches to OSS component adoption and the challenges businesses face establishing effective work practices to evaluate OSS components. We find businesses have established processes for evaluating OSS components and communities that support more complex and nuanced considerations of the cost and risks of component adoption alongside matters such as licence compliance and functional requirements. We also found that the increasing pace and volume of software development within some businesses provides pressure to continue to evolve software evaluation processes.

Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies.

Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solutions often limit the full brain-related assessments in real-life scenarios. Here we introduce the Biohub platform, a hardware/software (HW/SW) integrated wearable system for multistream synchronized acquisitions. This system consists of off-the-shelf hardware and state-of-art open-source software components, which are highly integrated into a high-tech low-cost solution, complete, yet easy to use outside conventional labs. It flexibly cooperates with several devices, regardless of the manufacturer, and overcomes the possibly limited resources of recording devices. The Biohub was validated through the characterization of the quality of (i) multistream synchronization, (ii) in-lab electroencephalographic (EEG) recordings compared with a medical-grade high-density device, and (iii) a Brain-Computer-Interface (BCI) in a real driving condition. Results show that this system can reliably acquire multiple data streams with high time accuracy and record standard quality EEG signals, becoming a valid device to be used for advanced ergonomics studies such as driving, telerehabilitation, and occupational safety.

Epidemic Location Intelligence System as Response to the COVID-19 Outbreak in Bosnia and Herzegovina

The outbreak of COVID-19 is a public health emergency that caused disastrous results in many countries. The global aim is to stop transmission and prevent the spread of the disease. To achieve it, every country needs to scale up emergency response mechanisms, educate and actively communicate with the public, intensify infected case finding, contact tracing, monitoring, quarantine of contacts, and isolation of cases. Responding to an emergency requires efficient collaboration and a multi-skilled approach (medical, information, statistical, political, social, and other expertise), which makes it hard to define one interface for all. As actors from different perspectives and domain backgrounds need to address diverse functions, the possibility to exchange available information quickly would be desirable. In Bosnia and Herzegovina, a joint state-level public health institution has not been established, but is covered by entity competencies. In this sense, a geoportal has been developed as an epidemiological location-intelligence system (ELIS) that supports the exchange of such information between the entities and the cantons. For its development, open source software components in the cloud were used as a working platform with all the necessary functionalities. The geoportal provides an entry point for access to geospatial, epidemiological, environmental and statistical data used for analysis, geocoding of confirmed COVID-19 cases, identification of disease dynamics, identification of vulnerable groups, mapping of health capacities, and general modeling of infection spread with application support for communication and collaboration between all institutions and the public. The paper describes the challenges and ways to overcome them in the development and use of ELIS.