Open Source Solutions Research Articles

Building and validation of a set of facial expression images to detect emotions: a transcultural study.

The automatic emotion recognition from facial expressions has become an exceptional tool in research involving human subjects and has made it possible to obtain objective measurements of the emotional state of research subjects. Different software and commercial solutions are offered to perform this task. However, the adaptation to cultural context and the recognition of complex expressions and/or emotions are two of the main challenges faced by these solutions. Here, we describe the construction and validation of a set of facial expression images suitable for training a recognition system. Our datasets consist of images of people with no experience in acting who were recorded with a webcam as they performed a computer-assisted task in a room with a light background and overhead illumination. The six basic emotions and mockery were included and a combination of OpenCV, Dlib and Scikit-learn Python libraries were used to develop a support vector machine classifier. The code is available at GitHub and the images will be provided upon request. Since transcultural facial expressions to evaluate complex emotions and open-source solutions were used in this study, we strongly believe that our dataset will be useful in different research contexts.

Modeling heat exchangers with an open source DEM-based code for granular flows

Dense granular flows exist in many solid particle heat exchangers and solar receivers studied in the field of Concentrating Solar Power (CSP). By tracking particles individually with the Discrete Element Method (DEM), the details of particle friction, collisions, and mixing can be modeled accurately. An open source DEM-based code for modeling heat transfer in dense granular flows is presented, called Dense Particle Heat Transfer (DPHT). It uses one-way coupling, with DEM run first to find the particle positions and DPHT run second to calculate heat transfer between particles and any walls. Heat transfer is computed with six sub-models, including effects from contact conduction, conduction through the thin fluid gap between particles, and thermal radiation. Simulations are run to investigate particle-particle radiation, with DPHT matching a full Monte Carlo ray tracing simulation to within 1.6%, whereas the “local environment temperature” models from literature show physically unrealistic results. As a test of the accuracy of DPHT, a simulation is run to replicate published experimental work, and results in terms of total heat transfer are within 4%. Finally, a tubular heat exchanger is analyzed, and a “radial” mixer design is introduced, increasing heat transfer by 8%. Several DEM-based heat transfer codes have been described in literature, but they are often kept in-house. Some open source codes exist as well, but they generally have drawbacks including missing heat transfer modes, insufficient flexibility to make significant changes, and incomplete documentation. DPHT aims to simplify this modeling method by providing a flexible, open source solution.

Open source audio platform ultrasound dosimeter

It is well known that hearing loss can occur from exposure to high intensities of sounds >80 dBA; however there is less information about hearing loss from ultrasonic frequencies. There are many commercial and industrial devices that produce ultrasonic acoustic energy ranging from humidifiers, pest and pet repellent devices, and crowd control devices. Even though there are fewer regulations with regard to ultrasound, there have been documented cases of effects including temporary or permanent threshold shifts from exposure to ultrasonic energy. However, there is not a readily available open source solution for quantifying exposure. In this work, a TYMPAN open source hearing aid development platform is used to develop and test a prototype ultrasonic dosimeter. This dosimeter works like a SPL meter, with the inclusion of the ultrasonic 1/3 octave bands, with an audible alarm emitted when the user happens to be in the presence of ultrasonic energy. From the full data recording of a test covering various environments, several key features of the exposure are highlighted. The presentation will cover the development of the algorithms, testing of the device, and post test analysis. Code will be made available via the open source libraries for future users to build upon.

Bibliometric analysis of Organisational Behaviour

This study aims to investigate the theoretical contributions on organisational behaviour and meritocracy. The methodology used involved exploratory analysis, based on bibliometric research. The data were extracted from the Scopus and Web of Science journal databases, accessed through the journals portal of the Coordination for the Improvement of Higher Education Personnel (CAPES) and through the restricted access of the Federated Academic Community (Café) of the Instituto Federal Goiano (IF Goiano). The result obtained indicated the combination of the search terms, "organisational behaviour and merit". (Scopus and Web of Science). It was used as technical support, a set of open source solutions, R software, with techniques for filtering duplicate and non-pertinent publications, totaling 63 articles, ranging from the years 2015 to June 2021. It is clear that there is a concentration of terms reporting on public educational organisations, which focus on issues about performance and the positive effects of human behaviour. Finally, it was identified that the term merit is closer to contexts involving perspectives, gender, and market, while meritocracy subsidizes studies that address organisational social inequality and human resource management.

Privacy-Aware Contact Sharing for Groups in P2P Networks

The need for peer-to-peer (p2p) communications is obvious because current centralized solutions are capturing and storing too much information from individuals communicating with each other. HELIOS platform introduces a new social media platform that is not controlled by any central operator but brings the power of possession of the data back to the users. It does not have centralized servers that store and handle receiving/sending of the messages. Instead, HELIOS platform relies on the current open-source solutions available in the p2p communities to propagate the messages to the wanted recipients of the data and/or messages. The authors of this paper propose a set of protocols to help answer one specific problem related to p2p communication. Especially, this paper proposes how to privately share data (end-point address or other) of the user with such other users who have previously connected with the user securely, either offline or online.

A non-traditional open-source solution for altmetrics

PurposeAltmetric carries the potential of highlighting scholarly content by measuring online interactions much before other forms of traditional metrics grow up. The aim of this paper is to be the single point of access for librarians, scientists, information specialists, researchers and other scholars in public to learn to embed the open-source embeddable badge provided by Altmetric in their websites and showcase their article altmetrics. Libraries can take advantage of this free and innovative tool by incorporating it in their own websites or digital repositories.Design/methodology/approachThis paper elucidates steps for embedding altimetric institutional repository badges in personal websites or institutional repositories.FindingsThis open-source Altmetric tool tracks a range of sources to catch and collect the scholarly activity and assists in monitoring and reporting the attention surrounding an author’s work in a very timely manner.Originality/valueThis tool is freely available to libraries worldwide.

Vulnerability Management Models Using a Common Vulnerability Scoring System

Vulnerability prioritization is an essential element of the vulnerability management process in data communication networks. Accurate prioritization allows the attention to be focused on the most critical vulnerabilities and their timely elimination; otherwise, organizations may face severe financial consequences or damage to their reputations. In addition, the large amounts of data generated by various components of security systems further impede the process of prioritizing the detected vulnerabilities. Therefore, the detection and elimination of critical vulnerabilities are challenging tasks. The solutions proposed for this problem in the scientific literature so far—e.g., PatchRank, SecureRank, Vulcon, CMS, VDNF, or VEST—are not sufficient because they do not consider the context of the organization. On the other hand, commercial solutions, such as Nessus, F-Secure, or Qualys, do not provide detailed information regarding the prioritization procedure, except for the scale. Therefore, in this paper, the authors present an open-source solution called the Vulnerability Management Center (VMC) in order to assist organizations with the vulnerability prioritization process. The VMC presents all calculated results in a standardized way by using a Common Vulnerability Scoring System (CVSS), which allows security analysts to fully understand environmental components’ influences on the criticality of detected vulnerabilities. In order to demonstrate the benefits of using the the open-source VMC software developed here, selected models of a vulnerability management process using CVSS are studied and compared by using three different, real testing environments. The open-source VMC suite developed here, which integrates information collected from an asset database, is shown to accelerate the process of removal for the critical vulnerabilities that are detected. The results show the practicability and efficacy of the selected models and the open-source VMC software, which can thus reduce organizations’ exposure to potential threats.

Fast and exact quantification of motif occurrences in biological sequences

BackgroundIdentification of motifs and quantification of their occurrences are important for the study of genetic diseases, gene evolution, transcription sites, and other biological mechanisms. Exact formulae for estimating count distributions of motifs under Markovian assumptions have high computational complexity and are impractical to be used on large motif sets. Approximated formulae, e.g. based on compound Poisson, are faster, but reliable p value calculation remains challenging. Here, we introduce ‘motif_prob’, a fast implementation of an exact formula for motif count distribution through progressive approximation with arbitrary precision. Our implementation speeds up the exact calculation, usually impractical, making it feasible and posit to substitute currently employed heuristics.ResultsWe implement motif_prob in both Perl and C+ + languages, using an efficient error-bound iterative process for the exact formula, providing comparison with state-of-the-art tools (e.g. MoSDi) in terms of precision, run time benchmarks, along with a real-world use case on bacterial motif characterization. Our software is able to process a million of motifs (13–31 bases) over genome lengths of 5 million bases within the minute on a regular laptop, and the run times for both the Perl and C+ + code are several orders of magnitude smaller (50–1000× faster) than MoSDi, even when using their fast compound Poisson approximation (60–120× faster). In the real-world use cases, we first show the consistency of motif_prob with MoSDi, and then how the p-value quantification is crucial for enrichment quantification when bacteria have different GC content, using motifs found in antimicrobial resistance genes. The software and the code sources are available under the MIT license at https://github.com/DataIntellSystLab/motif_prob.ConclusionsThe motif_prob software is a multi-platform and efficient open source solution for calculating exact frequency distributions of motifs. It can be integrated with motif discovery/characterization tools for quantifying enrichment and deviation from expected frequency ranges with exact p values, without loss in data processing efficiency.

A deep learning algorithm to detect and classify sun glint from high-resolution aerial imagery over shallow marine environments

Sun glint contamination is a significant problem for high-resolution remote sensing over aquatic environments. Sun glint is a particular issue for researchers using aerial imagery to assess shallow water benthic communities, as it may be wrongly classified as benthic substrates of interest. Although various methods are available to correct for sun glint using multispectral and hyperspectral imagery, no method has been developed to detect sun glint within high-resolution RGB imagery, such as that collected with drones. Here we developed an artificial neural network capable of automated detection of sun glint in high-resolution imagery. Training data were classified using an object-based image analysis workflow and a semantic image segmentation algorithm was developed based on a modified U-net architecture. The model correctly identified 99.58% of background in our test images, and 66.07% of sun glint in our test images. These accuracies were achieved despite a highly imbalanced dataset, with sun glint only accounting for 1.19% of pixels in the testing dataset. Overall, 99.18% of predictions in this model were correct. Given this, we contend that this algorithm is a simple solution for the instant detection of sun glint from high-resolution imagery. We offer this semantic image segmentation as an open source solution for the detection and classification of sun glint in high-resolution imagery.

Implementation of an Integrated Online Class Model using Open-Source Technology and SNS

Before Covid-19, the class model was divided into online, offline, and blended learning. Due to Covid-19, we have the only online class environment. We need a new online class model under the new circumstances. In the new model, all technology and educational methods need to be well-adapted, organized and harmonized to compensate for the absence of offline learning sessions. In this paper, we propose a new online class model. Because of the absence of offline sessions, the model emphasizes the integration of synchronous and asynchronous activities seamlessly and effectively. The model also emphasizes the instructor's role as a content prosumer because the instructor in the new model is either reusing other's and the one's own contents or supplying those contents for others. This model uses open-source solutions or free services like Moodle, OBS, Tubestory, and Snap Camera for both budget-saving and stability purposes. It actively uses Moodle's monitoring capability and adopts various learning technologies. It consists of three activity sessions: a pre-Zoom session, a Zoom session, and a post-Zoom session. Each session is composed of modules that describe the process and action for the class. The process, methods, and techniques for each module are explained in this paper. The official students survey for class evaluation held by Kongju national university showed that the new class model's application obtained a higher score than the same class of the previous year that is performed by conventional teaching.

3D printing of clay paste enhanced by scrap polymer from powder bed processes

PurposePowder bed additive manufacturing processes are widespread due to their many technical and economic advantages. Nevertheless, the disposal of leftover powder poses a problem in terms of process sustainability. The purpose of this paper is to provide an alternative solution to recycle waste PA12 powder from HP multi jet fusion. In particular, the opportunity to use this material as a dispersion in three-dimensional (3D) printed clay is investigated.Design/methodology/approachA commercial fused deposition modelling printer was re-adapted to extrude a viscous paste composed of clay, PA12 and water. Once printed, parts were dried and then put in an oven to melt the polymer fraction. Four compositions with different PA12 concentration were studied. First, the extrudability of the paste was observed by testing different extrusion lengths. Then, the surface porosities were evaluated through microscopical observations of the manufactured parts. Finally, benchmarks with different geometries were digitalised via 3D scanning to analyse the dimensional alterations arising at each stage of the process.FindingsOverall, the feasibility of the process is demonstrated. Extrusion tests revealed that the composition of the paste has a minor influence on the volumetric flow rate, exhibiting a better consistency in the case of long extrusions. The percentage of surface cavities was proportional to the polymer fraction contained in the mix. From dimensional analyses, it was possible to conclude that PA12 reduced the degree of shrinkage during the drying phase, while it increased dimensional alterations occurring in the melting phase. The results showed that the dimensional error measured on the z-axis was always higher than that of the XY plane.Practical implicationsThe method proposed in this paper provides an alternative approach to reuse leftover powders from powder bed fusion processes via another additive manufacturing process. This offers an affordable and open-source solution to companies dealing with polymer powder bed fusion, allowing them to reduce their environmental impacts while expanding their production.Originality/valueThe paper presents an innovative additive manufacturing solution for powder reuse. Unlike the recycling methods in the body of literature, this solution does not require any intermediate transformation process, such as filament fabrication. Also, the cold material deposition enables the adoption of very inexpensive extrusion equipment. This preliminary study demonstrates the feasibility and the benefits of this process, paving the way for numerous future studies.

Rapid Requirements Elicitation of Enterprise Applications Based on Executable Mockups

Software development begins with the requirements. Misunderstandings with customers in this early phase of development result in wasted development time. This work investigates the possibility of using executable UI mockups in the initial phases of functional requirements elicitation during the development of business applications. Although there has been a lot of research in the field in recent years, we find that there is still a need to improve model-driven tool design in order to enable customer participation from the initial phases of requirement specifications based on working prototypes. These prototypes can directly be reused in the rest of the development process. To meet the goal, we have been developing an open-source solution called Kroki that enables rapid collaborative development. We conducted a series of 10 joint user sessions with domain experts from different domains and backgrounds, resulting in the prototype specifications ranging from 7 to 20 screen mockups accompanied with domain models, developed in two-hour time frames. In this paper, we present our tool design that contributes to rapid joint development, and the results from the user sessions.

AN OPEN-SOURCE CANOPY CLASSIFICATION SYSTEM USING MACHINE-LEARNING TECHNIQUES WITHIN A PYTHON FRAMEWORK

Abstract. Studying deforestation has been an important topic in forestry research. Especially, canopy classification using remotely sensed data plays an essential role in monitoring tree canopy on a large scale. As remote sensing technologies advance, the quality and resolution of satellite imagery have significantly improved. Oftentimes, leveraging high-resolution imagery such as the National Agriculture Imagery Program (NAIP) imagery requires proprietary software. However, the lack of insight into the inner workings of such software and the inability of modifying its code lead many researchers towards open-source solutions. In this research, we introduce CanoClass, an open-source cross-platform canopy classification system written in Python. CanoClass utilizes the Random Forest and Extra Trees algorithms provided by scikit-learn to classify canopy using remote sensing imagery. Based on our benchmark tests, this new canopy classification system was 283 % to 464 % faster than commercial Feature Analyst, but it produced comparable results with a similarity of 87.56 % to 87.62 %.

NagareDB: A Resource-Efficient Document-Oriented Time-Series Database

The recent great technological advance has led to a broad proliferation of Monitoring Infrastructures, which typically keep track of specific assets along time, ranging from factory machinery, device location, or even people. Gathering this data has become crucial for a wide number of applications, like exploration dashboards or Machine Learning techniques, such as Anomaly Detection. Time-Series Databases, designed to handle these data, grew in popularity, becoming the fastest-growing database type from 2019. In consequence, keeping track and mastering those rapidly evolving technologies became increasingly difficult. This paper introduces the holistic design approach followed for building NagareDB, a Time-Series database built on top of MongoDB—the most popular NoSQL Database, typically discouraged in the Time-Series scenario. The goal of NagareDB is to ease the access to three of the essential resources needed to building time-dependent systems: Hardware, since it is able to work in commodity machines; Software, as it is built on top of an open-source solution; and Expert Personnel, as its foundation database is considered the most popular NoSQL DB, lowering its learning curve. Concretely, NagareDB is able to outperform MongoDB recommended implementation up to 4.7 times, when retrieving data, while also offering a stream-ingestion up to 35% faster than InfluxDB, the most popular Time-Series database. Moreover, by relaxing some requirements, NagareDB is able to reduce the disk space usage up to 40%.

MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization.

Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing options are available, however, both commercial and open-source solutions for data processing have limitations, such as vendor platform exclusivity and/or requiring familiarity with diverse programming languages. Data processing of untargeted metabolite data is a particular problem for laboratories that specialize in non-routine mass spectrometry analysis of diverse sample types across humans, animals, plants, fungi, and microorganisms. Here, we present MStractor, an R workflow package developed to streamline and enhance pre-processing of metabolomics mass spectrometry data and visualization. MStractor combines functions for molecular feature extraction with user-friendly dedicated GUIs for chromatographic and mass spectromerty (MS) parameter input, graphical quality-control outputs, and descriptive statistics. MStractor performance was evaluated through a detailed comparison with XCMS Online. The MStractor package is freely available on GitHub at the MetabolomicsSA repository.

HuBeRo - a Framework to Simulate Human Behaviour in Robot Research

Social robots' software is commonly tested in a simulation due to the safety and convenience reasons as well as an environment configuration repeatability assurance. An interaction between a robot and a human requires taking a person presence and his movement abilities into consideration. The purpose of the article is to present the HuBeRo framework, which can be used to simulate human motion behaviour. The framework allows independent control of each individual's activity, which distinguishes the presented approach from state-of-the-art, open-source solutions from the robotics domain. The article presents the framework assumptions, architecture and an example application with respect to presented scenarios.

Free Open-Source High – Availability Solution for Java Web Application Using Tomcat And MySQL

With the growth of the internet, the number of web applications is also growing. Many web applications are becoming more important to the stakeholders that they cannot afford downtime which can cause loss of revenue, loss of productivity, etc. In the past, only big organizations with deep pocket could afford implement high-availability for their web application, but nowadays there are free open-source software programs that support high-availability feature available to everyone. This research studied the feasibility of implementing high-availability for Java web application system without using commercial software. This research compared the capability of proprietary and free open-source high-availability solution for Java web application based on a simple high-availability design, where a test Java web application was deployed into the environment based on proprietary and free open-source solutions, and tested how well each solution perform when problem occurs. The result showed that the free open-source high-availability solution worked, but not as well as proprietary one. However, the proprietary high-availability solution for database did not perform well, and neither did the open-source one. This research concludes that the free open-source high-availability solution works and thus made high-availability become much more affordable, especially for individual or small organizations with budget constraints.

MAYGEN: an open-source chemical structure generator for constitutional isomers based on the orderly generation principle

The generation of constitutional isomer chemical spaces has been a subject of cheminformatics since the early 1960s, with applications in structure elucidation and elsewhere. In order to perform such a generation efficiently, exhaustively and isomorphism-free, the structure generator needs to ensure the building of canonical graphs already during the generation step and not by subsequent filtering. Here we present MAYGEN, an open-source, pure-Java development of a constitutional isomer molecular generator. The principles of MAYGEN’s architecture and algorithm are outlined and the software is benchmarked in single-threaded mode against the state-of-the-art, but closed-source solution MOLGEN, as well as against the best open-source solution PMG. Based on the benchmarking, MAYGEN is on average 47 times faster than PMG and on average three times slower than MOLGEN in performance.

Wheeled Robot with Ardublock Programming for Elementary School Students

Robotics technology can be implemented into the elementary school curriculum with the presence of extracurricular robotics or better as robotics only. Robotics in students is taught to assemble and program simple robots packaged in robotics learning media. Robotics activities basically use wheelled robots but have different functions. With the basic assumption of the robot, we can reduce the cost of procurement by making a robot with one wheel but with various functions. The wheeled robot is portable, so it is easy to disassemble. Robotics activities in generaly uses an Arduino controller with the C programming language. Elementary school students have difficulty understanding the language. Ardublock as one of the easy and open-source solutions. This research focused on the working system of a wheeled robot with various features (line tracer, transporter, and wall tracking) as well as the success in using ardublock logic as the programming language of the robot. The results test show that the ardublock program can be used to program the Arduino controller on the robot. The wheeled robot with the line follower feature recorded a travel time of 6.0 seconds on a 200cm trajectory. The wheeled robot with a transporter feature on a 200 cm trajectory takes an average of 8.9 seconds with the success of lifting objects 7 times out of 10 attempts.

3D MULTI-RESOLUTION MAPPING OF MARS USING CASP-GO ON HRSC, CRISM, CTX AND HIRISE

Abstract. Automated large-scale retrieval of stereo photogrammetric DTMs of Mars fall into three categories: use of COTS software such as BAE-SOCET®; private software such as the DLR-VICAR software suite and open source solutions such as the NASA Ames Stereo Pipeline (ASP). We describe here a novel open source system developed on the back of ASP known as CASP-GO (Tao et al., 2018) which has automated and extended ASP to be able to be applied to all modern single-pass or repeat-pass stereo photogrammetric datasets from 21st century systems such as HRSC, CTX and HiRISE, CASP-GO also includes an automated co-registration system which employs HRSC (itself linked to MOLA) as the base-map upon which all other DTMs are co-registered. We show an example here of this automated co-registration system applied to multi-resolution stacks including CRISM images. Several thousand multi-resolution 3D products, Digital Terrain Models (DTMs) and their corresponding orthorectified images (ORIs) have been generated and used in a wide variety of scientific studies, a few examples of which are shown here. Finally, a new method distributing these products providing long-term archiving and ease of access using DOIs is shown employing the ESA-PSA Guest Storage Facility and their corresponding display within the iMars webGIS system.