Open Source Research Articles

Development of a Large-Scale Horizontal Curve Inventory for Safety Analysis Using Open GIS Data

Abstract Horizontal curves are crucial for the safety and mobility of roadways. To enhance the understanding of these curves, transportation agencies are investigating methods to accurately determine their spatial locations, geometric attributes, and conditions within their extensive road networks. Leveraging the widespread availability of Global Positioning System (GPS) and Geographic Information System (GIS) data, significant advancements have been made in developing automated algorithms that identify horizontal curves from GPS trajectories and GIS basemaps. This study introduces a novel dataset—the Horizontal Curve Inventory—that encapsulates detailed features of horizontal curves. We employed a modified automated cycle regression algorithm designed for large-scale road network analysis to extract horizontal curve data. This method was applied nationally to process an expansive network utilizing open-source GIS basemaps, encompassing over 300,000 miles across interstate, U.S. highway, and state highway systems. The inventory includes comprehensive data on curve radius, rotation angle, start and end point coordinates, and the curve’s center points. These data are essential for supporting safety research pertaining to road alignment. Our approach demonstrated robust performance across various open GIS data sources and provides the first accurate, efficient, and comprehensive inventory of horizontal curves for all major highway systems in the United States. The dataset is available at http://aichengbo.com/research/national-horizontal-curve-inventory/.

Advancing urban health in Portugal: exploring liveability and its association with mental morbidity

Abstract Background As cities face challenges posed by urbanisation, it becomes essential to understand how city planning can contribute to protecting public health. In this study, we aimed to assess the liveability of different areas in Lisbon, Portugal, by developing a liveability index at the parish level. Secondly, we aimed to explore its association with hospitalisation due to mental disorders. Methods The liveability index was built based on the World Health Organisation’s Urban Health Index methodology. We obtained data on liveability related to housing, socio-economic conditions and access to services (e.g. healthcare) from the 2011 census and other open data sources for Lisbon’s parishes (n = 22). Data on hospital admissions due to mental disorders was sourced at the parish level from the national database for hospital morbidity for the period 2013-2016 and sex-age-standardised. Binomial negative regression was employed to estimate the association between the liveability index tertiles and observed hospital admissions. We used the expected number of hospitalisations as the offset variable and tested for spatial autocorrelation among the regression residuals. Results Our analysis showed that living in the most liveable parishes is associated with a significant decrease in the standardised admission ratio due to mental disorders, compared to living in the least liveable areas (Incidence Relative Ratio=0.643; 95% CI: 0.427, 0.967). We did not observe any geographical pattern in the regression residuals (Moran’s I= -0.035, p = 0.427). Conclusions Our findings show disparities in liveability among Lisbon’s parishes and identify a protective association between living in higher liveability areas and hospital admissions due to mental disorders. This work should prompt further studies concerning this subject to inform urban planning policies to improve liveability and equally reduce the risk of mental health-related harm within cities. Key messages • A spatial index to assess liveability in urban areas was developed. The association between the liveability of Lisbon’s parishes and hospital admissions due to mental disorders was explored. • We found a significant protective association between higher liveability and hospital admissions due to mental disorders. This work is relevant to inform the implementation of urban planning policies.

Recent One Decade Trends in Mathematical Representation Research: Systematic Mapping Study

Research can change over time and can be influenced by technological developments, educational trends, and current social issues. Developments on trends in mathematical representation research over the past 10 years are discussed in this systematic mapping study (SMS). The question of review research with the systematic mapping study method is how the trend of mathematical representation research over the last 1 decade and what new topics have the opportunity to be researched by future researchers related to the themes of mathematical representation. The method used in this review is the PRISMA method which includes 5 stages carried out: 1) defining eligibility criteria, 2) determining information sources, 3) data selection, 4) data collection, and 5) data collection. In this systematic mapping study, it starts from searching for articles on the topic of mathematical representation during the last 1 decade, namely the range of 2013-2023, articles obtained from the scopus database in July 2023 with the keywords "representations" AND : Mathematics" initial data obtained 1907 articles after the exclusion process obtained 120 articles which were then analyzed using R-Studio and Vos-Viewer tools. The results of SMS obtained the relationship of representation topics in the last 10 years of research with the topics of visual, computer software, computer aid instruction, data mining, open source software, network architecture, natural language processing systems, intelligent systems and information analysis. In addition, research over the past 1 decade on the topic of representation has led more to data mining, security of data and STEM. Artificial Intelligence or artificial intelligence is the latest topic that over the past 3 years has grown in various articles that deal with the theme of mathematical representation and accompanied by the theme of multi-representation. The evolution of research topics related to mathematical representations that used to be only related to visual representations and image representations now leads to computer programs, programming algorithms and artificial intelligence, this shows that over the past 1 decade there has been an evolution of research in the implementation of representations in technology.

Rancang Bangun Aplikasi Edukasi Reproduksi Manusia Pada Pelajar SMPN 187 Jakarta Berbasis Android

The implementation of education at SMPN 187 Jakarta is often limited to the use of PPT and RPP,causing the material to become monotonous and less interesting for students. Reproductioneducation is also often not delivered comprehensively, resulting in less than optimal studentunderstanding. To overcome this, an Android-based application was developed which aims toincrease students' understanding of reproductive health. This application provides educationalmaterial covering secondary and primary aspects as well as a test feature to measure studentunderstanding, making learning more effective and interactive. This application uses Flutter as amulti-platformframework andDart as an open source programming languagewithOOPconceptsthat are easy to understand. The application backend is managed with Laravel, functioning asBackendAPImanagement of themobile application.The prototypemethod is used in development,starting from collecting user needs to creating a design/prototype. The results of this research areas an educational application and learning support media for students at SMPN 187 Jakarta bymaking learning media flexible and efficient, with features for characters that help improvestudents' and female students' understanding of educational reproduction.

Environmental niche models improve species identification in DNA barcoding

Abstract Recent advances in DNA barcoding have immeasurably advanced global biodiversity research in the last two decades. However, inherent limitations in barcode sequences, such as hybridization, introgression or incomplete lineage sorting can lead to misidentifications when relying solely on barcode sequences. Here, we propose a new Niche‐model‐Based Species Identification (NBSI) method based on the idea that species distribution information is a potential complement to DNA barcoding species identifications. NBSI performs species membership inference by incorporating niche modelling predictions and traditional DNA barcoding identifications. Systematic tests across diverse scenarios show significant improvements in species identification success rates under the newly proposed NBSI framework, where the largest increase is from 4.7% (95% CI: 3.51%–6.25%) to 94.8% (95% CI: 93.19%–96.06%). Additionally, obvious improvements were observed when using NBSI on potentially ambiguous sequences whose genetic nearest neighbours belongs to another species or more than two species, which occurs commonly with species represented by single or short DNA barcodes. These results support our assertion that environmental factors/variables are valuable complements to DNA sequence data for species identification by avoiding potential misidentifications inferred from genetic information alone. The NBSI framework is currently implemented as a new R package, ‘NicheBarcoding’, that is open source under GNU General Public Licence and freely available from https://CRAN.R‐project.org/package=NicheBarcoding.

Approaches to Treating Knee Osteoarthritis: Surgery vs. Non-Surgery Treatment

Introduction: Knee Osteoarthritis (KO) is a progressive, chronic disease that damage the joint cartilage of a knee and leads to a changes in a anatomy of the joint. Both surgical and non-surgical methods are used to treat the disease. In this study, we will compare the invasive vs non-invasive methods of KO treatment. Objectives: The review and presentation of the current state of knowledge on Treating Knee Osteoarthritis, comparing surgery vs non-surgery methods. Material and Methods: Review of the studies available on open access sources at PubMed, Google Scholar and National Library of Medicine. Conclusions: Surgery approach for the Knee Osteoarthritis treatment are more durable, have better pain relief and treat casually the OA. Similar effects cannot be reached by non-surgery methods yet. However, there is a big promise in future studies about non-surgery methods, which can also raise a Quality of Life significantly and even avoid or postpone an operation in some groups of patients.

Modelling the Sea Surface of Cardigan Bay

The aim of this project was to model the sea surface of Cardigan Bay, to be able to expand upon QinetiQ’s current wave models, used within their radar assurance activities. The sea surface can cause unwanted detections, which is referred to as clutter. The sea is not the only source of clutter such as litter and birds, have an impact on the returns detected by the radar. This project explored two different approaches, modelling the propagation of waves and modelling the distribution of energy across the sea surface. The first approach explored two open source models, WAVEWATCH III and SWAN, and after having technical errors, two real world, existing examples of where these models were implemented were researched. This research showed a lot of promise, and would be worth expanding upon. The second approach looked into two recognised equations for calculating the energy density of the waves, and then calculating the significant wave height. Overall, modelling the propagation of waves would produce more representative results, particularly SWAN which was a model designed for coastal waters, however to set up the wave models fell outside of the scope of this project.

Phishing URL detection with neural networks: an empirical study

Cybercriminals create phishing websites that mimic legitimate websites to get sensitive information from companies, individuals, or governments. Therefore, using state-of-the-art artificial intelligence and machine learning technologies to correctly classify phishing and legitimate URLs is imperative. We report the results of applying deterministic and probabilistic neural network models to URL classification. Key achievements of this work are: (1) The development of a unique approach based on probabilistic neural networks that improves classification accuracy. (2) We show for the first time in URL phishing research that a machine learning model trained on a combination of open source and private datasets is successful in production. The dataset is constructed from open sources like Alexa, PhishTank, or OpenPhish and, most importantly, real-world production data from EasyDMARC. The daily validation of the model using daily reported URL data and corresponding labels, both from open-source platforms and private production, reach on average a 97% accuracy on the validation dataset, labeled by PhishTank, OpenPhish and EasdDMARC where possible mislabeled data can not be excluded and was not possible to check due to large number of URLs. Feature engineering was done without third-party dependencies. Lastly, the evaluation of both deterministic and probabilistic models shows high accuracy on short and long URLs, where short URLs are defined as having less than 50 characters.

Fire at Sea: A 70-year Review of Fire-Related Mass Casualty Events on U.S. Aircraft Carriers.

A major fire at sea is among the most devastating events that can occur while a U.S. Navy combatant vessel is underway. Since World War II, no attack on a large U.S. Navy capital ship has occurred during combat operations. However, increasing global tensions raise the threat of future peer adversary naval combat, and shipboard medical caregivers must be prepared for mass casualty events in the deployed maritime environment. To better prepare modern naval caregivers for this possibility, we reviewed mass casualty events from major fires aboard large U.S. Navy aircraft carriers from 1950 through 2020 to summarize available objective data and identify lessons learned. Underway fires from any cause aboard U.S. Navy aircraft carriers and large amphibious assault ships causing more than 10 casualties (injuries + deaths) were reviewed from 1950 through 2020 using available open access sources including literature review, the Naval Safety Command mishap database, and U.S. Navy Judge Advocate Manual reports. Of 246 fires identified, 27 met inclusion criteria resulting in 1,634 casualties with a combined crew mortality of 23% of those injured. In the 16 events with at least 1 death, 2.0% of the total crew was injured with a combined mortality of 28%. All mishaps occurred while underway during routine training or combat operations; none were caused by an enemy combatant attack. Those events affecting more than 5% of the crew were particularly devastating resulting in a mortality rate of 29% of 1,056 total casualties. Given that main medical spaces may be damaged or destroyed during major fires from any cause, identified lessons learned included the need for (1) distributed medical supplies, (2) flexible medical treatment locations throughout the ship, (3) specific training to prepare non-physician caregivers and non-medical first responders to provide burn and hemorrhagic shock resuscitation, airway management, and prolonged care at or near the point of injury, and (4) the prolonged holding capability of critically ill burned and injured patients if evacuation off the ships is unavailable. Shipboard fires underway pose a significant threat to crew safety with a mortality of nearly a quarter of those injured. These fire mass casualty events immediately overwhelm shipboard medical capabilities requiring a complex response from all hands beginning with non-medical first responders. Notably, all events occurred outside of direct enemy combat, potentially underestimating the impact and number of casualties of a shipboard fire during naval combat. Advances in peer weaponry and the threat of future conflict emphasize the need for pre-deployment burn care training for all shipboard medical caregivers as well as advanced airway and resuscitation training for non-physician caregivers. This review underscores the profound impact of shipboard fires on crew safety, highlighting the critical need for enhanced preparedness and response strategies to prepare for fire-related mishaps during routine operations and naval combat.

Automation of conceptual design and modification of aircraft type unmanned aerial vehicles using multidisciplinary optimization and evolutionary algorithms. Part 1: Methods and models

This paper proposes a method for selecting rational parameters for large-size aircraft-type unmanned aerial vehicles at the initial design stages using an optimization algorithm of differential evolution and numerical mathematical modeling of aerodynamic problems. The method assumes implementation of weight and aerodynamic balance in the main flight modes, it can consider aircraft-type unmanned aerial vehicles with one or two lifting surfaces, applies parallel calculations, and automatically generates a three-dimensional geometric model of the aircraft appearance based on the optimization results. A method for accelerating by more than three times the process of solving the problem of optimizing aircraft takeoff weight parameters by introducing the target function into the set of design variables is proposed and demonstrated. The results of assessing the reliability of the mathematical models used for aerodynamics and the correct calculation of the target function are presented, taking into account various constraints. A comprehensive check of the operability and effectiveness of the method were considered by solving demonstration problems by optimizing more than ten main design parameters of the appearance of two existing heavy-class unmanned aerial vehicles with known characteristics from open sources. Examples of using the optimization results to modify prototypes are provided.

Open-Source Solutions in Archival Institutions

Open-source solutions offer a cost-effective alternative for archival institutions facing budget constraints. The absence of licensing fees and the ability to modify and customize the software without vendor lock-in make open source particularly appealing. This financial flexibility allows institutions to allocate resources to other critical aspects of preservation and access. In the article the author presents various advantages and disadvantages of using open-source software.

Machine learning analysis of high-repetition-rate two-dimensional Thomson scattering spectra from laser-produced plasmas

Abstract With the emergence of high-repetition-rate two-dimensional Thomson scattering (TS) measurements, improving spec- tral data analysis is a key area of interest. We present a new way to derive the electron temperature and density of laser-driven blast waves in plasmas from their TS spectra with machine learning (ML). This analysis occurs in both the non-collective (α < 1) and collective (α > 1) scattering regimes with the goal of autonomously and more accurately determining Te and ne both where spectral data has been collected and to give the ability to predict these attributes in regions where data has not been collected. We introduce three ML models, one trained only on experimental data, one only on synthetic data, and one using transfer learning, and compare their speed and accuracy with the conventional TS inversion algorithms in the open source PlasmaPy python package.

HMLB: Holonic multi-agent approach for preventive controllers load-balancing in SDN-enabled smart grid

Smart grid networks present advantages like improving reliability, security, scalability, etc. However, designing an efficient communication infrastructure for smart grid networks is a great challenge. This is because of its dependency on proprietary protocols and specific vendors. Software-defined-enabled smart grid (SDN-SG) tackles this problem by incorporating diverse protocols and standards including open source platforms. One of the most important questions in Software-defined Networking (SDN) is the controller placement problem being NP-Hard in nature. Therefore, the predominant goal of this paper is to diminish the time complexity by modeling the controller placement problem based on the holonic multi-agent system. The hierarchical structure of a holonic organization improves the computational complexity through the divide and conquer mechanism. Such an idea also decreases the distributed controllers' synchronization overhead which is an issue in the realm of SDN. On the other hand, the proper functioning of the smart grid has a strict dependency on time-critical services. Accordingly, the controller placement is supposed to be a Quality of Service-aware (QoS-aware) one. Also, intermittent topology changes in the smart grid and the occasional joining and leaving of members result in an unsteady traffic pattern and dynamicity of controller load. This research is a pioneer in providing a QoS-aware and dynamic controller placement mechanism for SDN-SG. Experimental results certify the preponderance of the approach over similar ones concerning computational complexity, packet loss, controllers’ synchronization overhead, and also load-balancing overhead.

ExoLyn: A golden mean approach to multispecies cloud modeling in atmospheric retrieval

Clouds are ubiquitous in exoplanets' atmospheres and play an important role in setting the opacity and chemical inventory of the atmosphere. Understanding clouds is a critical step in interpreting exoplanets' spectroscopic data. The aim is to model the multispecies nature of clouds in atmospheric retrieval studies. To this end, we developed -- a 1D cloud model that balances physical consistency with computational efficiency. solves the transport equation of cloud particles and vapor under cloud condensation rates that are self-consistently calculated from thermodynamics. is a standalone, open source package capable of being combined with optool to calculate solid opacities and with petitRADTRANS to generate transmission or emission spectra. With we find that the compositional structure of clouds in hot Jupiter planets' atmospheres is layered with a cloud dominated by magnesiumsilicates on top of an iron cloud. This finding is consistent with more complex cloud formation models but can be obtained with in only a few seconds. The composition of the cloud particles can be constrained from the spectrum, for example MgSiO3 and Mg2SiO4 components give rise to an absorption feature at $8-10\ m $. We investigate the dependence of the cloud structure on the bulk elemental composition of the planet and find that SiO2 -dominated clouds form on metal-rich planets and Fe clouds with a strong extinction effect form on C-rich planets. Designed toward maximum flexibility can also be used in retrieval analysis of sub-Neptunes and self-luminous planets. The efficiency of opens the possibility of joint retrieval of exoplanets' gas and cloud components.

PENGELOLAAN KOLEKSI MUSEUM MUSIK INDONESIA BERBASIS APLIKASI OPEN SOURCE

The Indonesian Music Museum stores various music collections in the form of cassettes, compact discs, vinyl records, and music-related books. This self-managed museum has the potential to become an institution that stores musical works from various countries. Management has been carried out properly, starting from inventory of collections to registration, but still manually. The implementation of the Senayan Library Management System (SLiMS), which is an open source based application, is one solution for managing collections more quickly and making it possible to access them remotely. The method used in this research is a qualitative study using observations and interviews so that it can produce an appropriate management system for the museum. The main informants are museum managers who are considered to understand the metadata needs of their museum collections. All results of observations and interviews are used as guidelines in determining any changes to the applications used to manage collections at the Indonesian Music Museum. This research produces an open source application-based museum collection inventory system. Several changes and adjustments were made to this application so that it could be implemented in the museum. Terms referring to library collections were changed and adapted to the use of terms relevant to music collections. The grouping of collections based on music genres and artists' regions of origin which is usually carried out by the museum is still maintained to become the characteristic of this museum itself. The Indonesian Music Museum can implement this application in a sustainable and long-term manner. Using this system helps the museum to obtain data records of collections and their movements, as well as inventory data on collections currently owned.

Respiratory sarcopenia: aspects of pathogenesis, approaches to diagnosis

The severe course of infectious and inflammatory diseases of the respiratory system, high rates of morbidity and mortality among the elderly and senile aged people may be associated with respiratory sarcopenia, a new nosological form that describes age-related changes in the strength and structure of the respiratory muscles. The aim of the review is to update the data of open access scientific sources on aspects of pathogenesis and diagnostic approaches to respiratory sarcopenia. Foreign and domestic scientific publications on this topic were analyzed from 2019 to the present. The mechanisms of respiratory sarcopenia pahogenesis were assessed in the light of its relationship with whole body sarcopenia, age-related mechanisms of aging of the respiratory system as a whole, risk factors and lifestyle aspects of the elderly. The currently proposed diagnostic algorithm for respiratory sarcopenia is considered in detail. Conclusion. Age-related changes in muscle tissue also affect the respiratory muscles. Whole-body sarcopenia, according to some authors, may be accompanied by respiratory sarcopenia. The proposed terminology and algorithm for diagnosing this pathology require additional data accumulation and further discussion.

At First Sight! Zero-shot Classification of Astronomical Images with Large Multimodal Models

Abstract Vision-Language multimodal Models (VLMs) offer the possibility for zero-shot classification in astronomy: i.e., classification via natural language prompts, with no training. We investigate two models, GPT-4o and LLaVA-NeXT, for zero-shot classification of low-surface brightness galaxies and artifacts, as well as morphological classification of galaxies. We show that with natural language prompts these models achieved significant accuracy (above 80% typically) without additional training/fine tuning. We discuss areas that require improvement, especially for LLaVA-NeXT, which is an open source model. Our findings aim to motivate the astronomical community to consider VLMs as a powerful tool for both research and pedagogy, with the prospect that future custom-built or fine-tuned models could perform better.

Research on New Spatial Data Infrastructure Supports the Circulation of Geographic Information Data Elements

Abstract. Data is an important factor of production in the digital economy era and an important support for building a new development pattern. As an important part of data resources, geographic information data is also an important new factor of production, which plays a unique role in the construction of digital China and economic and social development. From the perspective of releasing the value of data elements, data infrastructure is a new type of infrastructure that provides integrated data aggregation, processing,circulation, application, operation, and security services for society under the support of network, computing power and other facilities. It is an organic whole covering hardware, software, open source protocols, standards, and mechanism design. Spatial data infrastructure (SDI) is a collection of technologies, policies and systems that realize the access and access of spatial data. Through the construction of new spatial data infrastructure (NSDI), it supports the circulation of geographic information data elements,making it an important part of data infrastructure. Firstly, this paper gives the connotation of geographic information data elements circulation. Secondly, it proposed to construct the circulation system of geographic information data elements on the basis of enumerating and summarizing the spatial data infrastructure, in order to better support the construction of digital China and economic and social development. Thirdly, the basic requirements, technical indicators and overall architecture of NSDI are designed. Finally, the opportunities and challenges faced by the circulation of geographic information data elements were summarized, mainly focusing on the aspects of policy mechanisms and security systems. At the end of the paper is a summary and acknowledgments.

Leveraging cloud compute and open source software to generate 3D models from drone photography

Abstract. Modern drone platforms provide the opportunity to capture large quantities of high quality, geotagged aerial imagery quickly and over large distances, at a relatively low cost. As organisations increasingly turn to digital twin technology to manage their operations, rich, photorealistic three dimensional (3D) models of their assets become increasingly important. This paper describes how cloud computing, and container based serverless compute in particular, can be used together with open source software to generate a 3D model, converted to 3D tiles for optimised transmission, from images of large outdoor assets captured by drone. This approach offers a flexible and cost effective way to processing drone imagery into 3D models whilst allowing you to maintain ownership and control of your data.

Entwicklung eines automatischen Open-Source-Werkzeugwechslers

Abstract Open source machine tools (OSMT) have the potential to democratize manufacturing by lowering access barriers, enabling new modes of value creation. However, there is still a lack of an open source automatic tool changer (ATC), due to its inherent complexity in terms of mechanical design and control. An ATC system is crucial for automating manufacturing processes that require multiple operations with different tools for a complete production step. This paper describes the design of a fully open source ATC concept, detailing its mechanical design and control schematic.