Free Tool Research Articles

Free Simulation Tools for Power Quality and Grid-Integration of Renewable Energies Cases

The analysis of Power Quality issues and/or the integration of renewable energy into the grid requires the use of different tools, among which the use of computer simulation applications stands out. The basic objective is to obtain a model of the electrical system under study that allows for knowledge, with a reasonable degree of precision, of its behavior under different operating conditions. The benefits of these tools are manifold, since they allow us to understand the response of the system, both in transient and steady-state conditions, to situations that are difficult to reproduce in practice: short circuits, failures in generation, transmission and distribution infrastructures, etc. Additionally, these tools can be used as platforms for operator training and network planning. Currently, a wide variety of commercial tools that are de facto standards can be found on the market. Some of these tools have a high cost and cannot be used by students outside the academic environment. In parallel, and thanks to the efforts of the scientific community, simulation tools have been developed that are available free of cost under several licensing models. This contribution analyzes some of the available tools, with special attention to those that are published under several open source and academic non-commercial software licenses that are available to the academic community free of cost.

Optimizing Patient Record Linkage in a Master Patient Index Using Machine Learning: Algorithm Development and Validation

Background To provide quality care, modern health care systems must match and link data about the same patient from multiple sources, a function often served by master patient index (MPI) software. Record linkage in the MPI is typically performed manually by health care providers, guided by automated matching algorithms. These matching algorithms must be configured in advance, such as by setting the weights of patient attributes, usually by someone with knowledge of both the matching algorithm and the patient population being served. Objective We aimed to develop and evaluate a machine learning–based software tool, which automatically configures a patient matching algorithm by learning from pairs of patient records previously linked by humans already present in the database. Methods We built a free and open-source software tool to optimize record linkage algorithm parameters based on historical record linkages. The tool uses Bayesian optimization to identify the set of configuration parameters that lead to optimal matching performance in a given patient population, by learning from prior record linkages by humans. The tool is written assuming only the existence of a minimal HTTP application programming interface (API), and so is agnostic to the choice of MPI software, record linkage algorithm, and patient population. As a proof of concept, we integrated our tool with SantéMPI, an open-source MPI. We validated the tool using several synthetic patient populations in SantéMPI by comparing the performance of the optimized configuration in held-out data to SantéMPI’s default matching configuration using sensitivity and specificity. Results The machine learning–optimized configurations correctly detect over 90% of true record linkages as definite matches in all data sets, with 100% specificity and positive predictive value in all data sets, whereas the baseline detects none. In the largest data set examined, the baseline matching configuration detects possible record linkages with a sensitivity of 90.2% (95% CI 88.4%-92.0%) and specificity of 100%. By comparison, the machine learning–optimized matching configuration attains a sensitivity of 100%, with a decreased specificity of 95.9% (95% CI 95.9%-96.0%). We report significant gains in sensitivity in all data sets examined, at the cost of only marginally decreased specificity. The configuration optimization tool, data, and data set generator have been made freely available. Conclusions Our machine learning software tool can be used to significantly improve the performance of existing record linkage algorithms, without knowledge of the algorithm being used or specific details of the patient population being served.

A novel wide scale well-baby clinic mobile application: an Egyptian pilot study

BackgroundUtilization of under 5-year-old child healthcare services in Egypt is considered low, the highest proportion of well-baby visits is mainly for immunization in the first 2 years of age. Mobile health (mHealth) interventions have the potential to be a useful and low-cost way to disseminate information about proper nutrition, can be used to monitor children’s growth using the official charts of World Health Organization, can also help in accessing vaccine-related information and schedules.ObjectivesTo assess needs and requirements for a new comprehensive well-baby clinic mobile application (app) covering well-baby clinic service components. Thereafter, to develop the app prototype and validate it.MethodsThis study was conducted in four phases: User requirements, development, validation and usage. In user requirement phase, the need for the new app was assessed by performing literature review, market app research and an online survey. In development phase, we developed the novel well-baby clinic app that constituted all well-baby clinic services for children’s health monitoring relying on evidence-based information and honoring data safety. In validation phase, after a series of testing, the app was validated using Mobile app rating scale (MARS) by public health and pediatrics consultants to assess its quality. Finally, the app was launched and made available to the public on Android platform.ResultsSehhat Tefly app was developed based on the demands and requirements of mothers of under 5-year-old children. The app constituted caregiver, child information and seven service elements: physical growth, developmental milestones, immunizations, nutrition, teething, safety & emergency measures and report. The app quality mean was rated 3.7 out of 5 by the panel of experts. The app was downloaded 1445 times in a 4 month period.ConclusionsSehhat Tefly app can meet the need for a free, easy and accessible tool for caregivers to track the progress of children’s development and wellbeing. It can also provide advice for referral to physician consultation in case of deviation from normal measures.

Numerical and experimental study of natural convection heat transfer on flat and corrugated plates

PurposeThe purpose of this study is to numerically and experimentally investigate the natural convection heat transfer in flat plates and plates with square, trapezoidal and triangular corrugations.Design/methodology/approachThis work is an extension of the previous studies by Verderio et al. (2021a, 2021b, 2021c, 2021d, 2022a). An experimental apparatus was built to measure the plates’ temperatures during the natural convection cooling process. Several physical parameters were evaluated through the experimental methodology. Free and open-source computational tools were used to simulate the experimental conditions and to quantitatively and qualitatively evaluate the thermal plume characteristics over the plates.FindingsThe numerical results were experimentally validated with reasonable accuracy in the range of studied for the different plates. Empirical correlations of , and , with good accuracy and statistical representativeness, were obtained for the studied geometries. The convective thermal efficiency of corrugated plates (Δη), as a function of , was also experimentally studied quantitatively. In agreement with the findings of Oosthuizen and Garrett (2001), the experimental and numerical results proved that the increase in the heat exchange area of the corrugations has a greater influence on the convective exchange and the thermal efficiency than the disturbances caused in the flow (which reduce ). The plate with trapezoidal corrugations presented the highest convective thermal efficiency, followed by the plates with square and triangular corrugations. It was also proved that the thermal efficiency of corrugated plates increases with .Practical implicationsThe results demonstrate that corrugated surfaces have greater thermal efficiency than flat plates in heating and/or cooling systems by natural convection. This way, corrugated plates can reduce the dependence on auxiliary forced convection systems, with application in technological areas and Industry 4.0.Originality/valueThe empirical correlations obtained for the corrected Nusselt number and thermal efficiency for the corrugated plate geometries studied are original and unpublished, as well as the experimental validation of the developed three-dimensional numerical code.

1517-P: Interactive Calculator to Estimate Insulin Sensitivity (IS) in Type 1 Diabetes

Introduction: Euglycemic hyperinsulinemic clamps, although costly, time- and labor-intensive, are “gold standard” in measuring insulin sensitivity (IS). Several formulae to estimate IS in people with Type 1 diabetes (T1D) exist (DOI: 10.1007/978-3-030-81303-1_18-1), using various routine and research assays, and with wide ranging IS results. Aim: To develop a free online tool to estimate IS using different metrics and existent formulae and compare estimated IS with measured glucose disposal rate (GDR) from 104 clamp studies. Methods: We prepared an online tool for calculating IS using 17 formulae. Suitable formula(e) are suggested based on available (clinical and research) data. We also compare calculated IS with measured IS (GDR) from clamp studies in 104 adults with T1D (mean±SD) age 34±7 yrs, T1D duration 10±4 yrs, HbA1c 7.7±1.5%, 33 with microvascular complications). Logistic regression was used to infer probability of calculated IS being below GDR=4.45 mg/kg/min or above GDR=6.5 mg/kg/min, which represent respectively the median and 75th percentile of measured GDR values. Results: A calculator is available at www.bit.ly/estimated-GDR and an example result in the Figure 1. Estimated IS varied widely, but results interpretation is generally consistent. Conclusion: We developed an interactive tool to estimate IS in T1D for clinical and research use. Disclosure A.S.Januszewski: None. P.Niedzwiecki: None. N.Sachithanandan: None. G.M.Ward: None. D.N.O'neal: None. D.Zozulinska-ziolkiewicz: Advisory Panel; Abbott, Lilly, Lilly, Novo Nordisk, Medtronic, Speaker's Bureau; Abbott, Ascensia Diabetes Care, Novo Nordisk, Medtronic, Boehringer-Ingelheim, AstraZeneca. A.Uruska: Other Relationship; Lilly, Boehringer-Ingelheim, AstraZeneca, Ascensia Diabetes Care, Sanofi. A.Jenkins: Advisory Panel; Insulet Corporation, Board Member; Insulin for Life, Research Support; Abbott Diabetes, Medtronic, Hemsley Charitable Trust, Juvenile Diabetes Research Foundation (JDRF), National Institutes of Health.

Enhancing terpene and other plant volatiles analysis – A free spreadsheet tool “Retentify” for GC–MS data processing

Despite significant progress in gas chromatography-mass spectrometry (GC–MS), misidentifications still occur, especially in untargeted analyses of complex samples of plant origin. In addition to using reference materials, a common approach to confirm identifications is to employ linear retention indices (LRIs). Ideally, when LRI validation is made automatically by the software using accurate library data. However, present solutions in this area either require additional payment or have many constraints. As a result, reference LRIs are often not included in search algorithms, or if they are, library LRI values may not be matched to the selectivity of the column used. Many GC–MS analyses are conducted without LRI comparison, or the comparison is performed after an MS library search. Such a manual examination is highly laborious, especially for datasets containing hundreds or more components. Therefore, an easy-to-use spreadsheet tool was developed to be used after an MS library search. The tool called Retentify, among other features, can: (1) calculate the experimental RIs, (2) retrieve automatically reference RIs from the reliable compilation of Babushok et al. (NIST), considering an appropriate selectivity of the column, (3) compute experimental LRIs errors and indicate the potential mismatch in the red/yellow/green color scale. Retentify is thoroughly described and demonstrated in the analysis of true lavender (Lavandula angustifolia) essential oil. The uniqueness of this tool lies in its reliance on highly accurate, averaged retention data provided by NIST, automatic input of reference LRIs based on CAS, and visuals to help LRI evaluation. The tool is easy to use and requires no financial and minimal time investment to learn, making it accessible to any researcher without specialization in plant volatile analysis.

File type identification tools for digital investigations

Digital forensics is the process of identifying, preserving, analyzing, and documenting digital evidence for investigation purposes. Building or using file analysis tools is of great interest for a forensic expert to collect high-level information in a short time. In this paper, we consider the examination of files contained in digital media, especially files with possible incorrect types. This often reveals a simple way to hide sensitive content such as porn images, passwords, or accounts. Many commercial and free forensic tools are available for file type identification (FTI). In this work, we assess the performance of ten of them on two significant datasets and scenarios. The main issue we address is the relevance of the tools for forensic purposes. The underlying question is: do expectations meet reality? Our experiments highlight the significant disparity in the accuracy and behavior of the studied tools.

Factors affecting college freshmen's YouTube acceptance for learning purposes

PurposeThere are a variety of benefits associated with the use of YouTube for learning purposes, such as YouTube is a free open-access tool students can use to facilitate their learning. This study investigates whether an attitudinal factor (i.e. perceived usefulness) and the factor's antecedents, resource quality factors (i.e. credibility, currency, coverage and relevance), normative factor (i.e. subjective norm) and control factor (i.e. perceived ease of use) all affect college freshmen's behavioral intentions to use YouTube for academic learning purposes.Design/methodology/approachThis research employs the theory of planned behavior (TPB) to explore the attitudinal, normative and control factors associated with college freshmen's behavioral intentions to use YouTube for academic learning. After developing a quantitative survey given to 182 college freshmen in a Southeastern institution in the United States of America, structural equation modeling (SEM) was used to examine the seven hypotheses and the research constructs.FindingsThe results indicate that attitudinal factor (i.e. perceived usefulness) and its antecedents, resource quality factors (i.e. currency, coverage and relevance) and normative factor (i.e. subjective norm) have a statistically significant effect on college freshmen's intentions to use YouTube for academic learning purposes.Research limitations/implicationsThis study suggests that individual motivations (i.e. perceived usefulness and subjective norm) and resource quality factors (i.e. currency, coverage and relevance) play into college freshmen's decisions to use YouTube for learning purposes, while other research indicates that the system or application itself factors into students' decisions to use technology for learning.Practical implicationsThis study suggests that college freshmen are more likely to use YouTube for academic learning purposes when the freshmen hold favorable attitudes about the platform and when the freshmen believe the freshmen's peers are also using YouTube to supplement in-class learning.Originality/valueThis is an initial study that focuses on college freshmen's behavioral intentions to use YouTube for academic learning purposes. This research demonstrates the roles that peers as well as resource quality factors play in students' decisions to use specific technology to enhance the students' learning.

Data 4 Climate Action Edinburgh

Data 4 Climate Action Edinburgh is a group of volunteers, donating our time and skills with data to support climate action and biodiversity in and around Edinburgh. The formation of the group was the idea of Pauline Ward, inspired on hearing discussions about the how climate action groups could be supported, and how they could help each other, through regional networks. Discussions with the Edinburgh Voluntary Organisations Council and the Scottish Secretariat for Climate Action Networks identified a role for D4CAE as part of such a network in Edinburgh. The Scottish Government has been working on a programme of support for such regional networks, the first being North East Scotland Climate Action Network. Specifically, there appeared to be great potential in facilitating the making of connections between local climate groups and prospective volunteers from among the staff and students of the University of Edinburgh. With practical support and dialogue with the University of Edinburgh Sustainability team and Community Engagement team, D4CAE carried out a survey of members of the public at the Edinburgh Climate Festival 2022. Underneath the University gazebo, individuals volunteered to help and talked with us about what areas of work would be most worthwhile in their view. The participants indicated their choices by placing chips into paper cups labelled with the options ‘mapping’, ‘sharing’ etc. The top result was ‘storytelling with data’. Volunteers asked us to create a mailing list so they could keep in touch and help. Climate activists told us they wanted help with presenting data about their activities for inclusion in funding bids, and mapping. We now have a facebook page, website and a github repository. We use free tools from Google for email and file sharing (Drive, Sheets, Docs). We hold a monthly online drop-in on Zoom. We’re working on building links into the university, and working with data. Biggest challenges – Many of our contacts who want to help are doing so in a professional capacity, and therefore mostly available during office hours, while the volunteer effort happens outside of working hours. Meanwhile, making the local groups aware of our offer is an area we need to work on, in partnership with the climate action network which is evolving and taking shape. Looking ahead – hoping to organise a datathon event near or at the university in the near future. Delivering skills – we’re in the business of sharing skills, and building our own skills with data along the way. We have fielded requests for help with non-climate data, both from professional life science researchers looking for help with data visualisation, and others through the community engagement network. The experience suggests there may be potential for a platform and other work to build more links for voluntary organisations to find help with specialised skills among the staff and students of the university.

Precision comparison for Different GNSS PPP solution using online services and open-source software processing

In order to properly post-process data from the Global Navigation Satellite System, it is crucial to evaluate the dependability by means of online free processing tools because the development of GNSS offers satellite navigation consumers around the globe promising benefits. The purpose of the study is to assess the precision of several online processing tools, including GSIPOST, AUSPOS, IBGE, Magic GNSS, CSRS-PPP, and open-source software. Three stations' worth of RINEX 2 data were subjected to field observations utilising GNSS observations from IGS, with an observation time of 30 seconds. After that, both online and open-source software was used to analyze the collected data, using GPS and GPS and GLONASS. The relative differences and accuracy of the coordinates generated by each software were then assessed by comparison with those acquired from reference stations. coordinates in the ITRF14 standard for the X, Y, and Z directions. Online GNSS processing services don't require GNSS data processing skills and are easy to use, and provide more accurate results for engineering and geodetic uses. RINEX 3 data must be checked for better resolution.

Capturing and Documenting the Wider Health Impacts of the COVID-19 Pandemic Through the Remember Rebuild Saskatchewan Initiative: Protocol for a Mixed Methods Interdisciplinary Project.

In the Canadian province of Saskatchewan, the global COVID-19 pandemic appeared amidst existing social health challenges in food insecurity, housing precarity and homelessness, poor mental health, and substance misuse. These chronic features intersected with the pandemic, producing a moment in time when the urgency of COVID-19 brought attention to underlying shortcomings in public health services. The objectives of the program of research are (1) to identify and measure relationships between the pandemic and wider health and social impacts, namely, food insecurity, housing precarity and homelessness, and mental health and substance use in Saskatchewan, and (2) to create an oral history of the pandemic in Saskatchewan in an accessible digital public archive. We are using a mixed methods approach to identify the impacts of the pandemic on specific equity-seeking groups and areas of social health concern by developing cross-sectional population-based surveys and producing results based on statistical analysis. We augmented the quantitative analysis by conducting qualitative interviews and oral histories to generate more granular details of people's experiences of the pandemic. We are focusing on frontline workers, other service providers, and individuals within equity-seeking groups. We are capturing digital evidence and social media posts; we are collecting and organizing key threads using a free open-source research tool, Zotero, to trace the digital evidence of the pandemic in Saskatchewan. This study is approved by the Research Ethics Board at the University of Saskatchewan (Beh-1945). Funding for this program of research was received in March and April 2022. Survey data were collected between July and November 2022. The collection of oral histories began in June 2022 and concluded in March 2023. In total, 30 oral histories have been collected at the time of this writing. Qualitative interviews began in April 2022 and will continue until March 2024. Survey analysis began in January 2023, and results are expected to be published in mid-2023. All data and stories collected in this work are archived for preservation and freely accessible on the Remember Rebuild Saskatchewan project's website. We will share results in academic journals and conferences, town halls and community gatherings, social and digital media reports, and through collaborative exhibitions with public library systems. The pandemic's ephemeral nature poses a risk of us "forgetting" this moment and the attendant social inequities. These challenges inspired a novel fusion among health researchers, historians, librarians, and service providers in the creation of the Remember Rebuild Saskatchewan project, which focuses on preserving the legacy of the pandemic and capturing data to support an equitable recovery in Saskatchewan. DERR1-10.2196/46643.

What goes before the CART? Introducing classification trees with Arbor and CODAP

AbstractThis volume is largely about nontraditional data; this paper is about a nontraditional visualization: classification trees. Using trees with data will be new to many students, so rather than beginning with a computer algorithm that produces optimal trees, we suggest that students first construct their own trees, one node at a time, to explore how they work, and how well. This build‐it‐yourself process is more transparent than using algorithms such as CART; we believe it will help students not only understand the fundamentals of trees, but also better understand tree‐building algorithms when they do encounter them. And because classification is an important task in machine learning, a good foundation in trees can prepare students to better understand that emerging and important field. We also describe a free online tool—Arbor—that students can use to do this, and note some implications for instruction.

Land suitability assessment of soils using geographic information system in the semi-arid area of Tunisia

Land suitability maps are useful tools for protecting soil resources. The main objective of this study was to elaborate and assess soil suitability maps for different rainfed and irrigated crops. This study was conducted in the North-East area of Tunisia, three speculations were adopted (Cereals, arboriculture and vegetable crops) in both rainfed and irrigated conditions. Arithmetic multiplication methods were used based on Food and Agriculture Organization (FAO) classification based on Free and Open Source Geographic Information System (QGIS) tools and soil pedological properties, slope, elevation and climatic data. Overall, regardless of rainfed or irrigated conditions, results showed that the studied soils were particularly suitable (S1) for cereals crops and marginal suitable (S3) for arboriculture crops with 20.44 and 23.71%, respectively. More particular, we registered an improvement in soil land suitability under irrigated conditions for cereals with 28.63%. The findings indicated that using the GIS system, the soil in the study area is more suitable for cereals and then for arboriculture under irrigated conditions, which requires some improvement in use strategies and good management of the soil resources. In our study area, where agricultural productivity and environmental and the impact of climate change are in a struggle, classifying land on the basis of soil capacity and suitability could help define the best agricultural practices to apply in order to preserve soil functions could help define the best agricultural practices to be applied in order to preserve soil functions.

Pre-Feasibility Assessment Tool for Solar Industrial Process Heating

The industrial sector demands 25% of global energy as heat, where one-third is used at temperatures below 150 °C. Nevertheless, the installed solar heating capacity in the industry is only 0.02%, even though the integration of solar heating systems into production processes could significantly reduce fossil fuel consumption at a competitive cost. Among other reasons, this low penetration is due to the final users’ lack of knowledge of solar heating technologies. As a result, a free pre-feasibility assessment tool was developed for non-specialised users to evaluate the possibility of integrating solar heat into their processes using basic information. This tool uses transient simulation to estimate a feasible solar heating system through the parametric optimisation of the solar collection area, thermal storage volume, heat exchange capacity, and solar integration schemes at the supply level and costs. A commercial facility in Mexico was analysed using the developed tool as a case study. However, even when this is not a design tool, the calculated solar collector area, storage tank volume, and investment were only 2.1%, 9.0%, and 2.3% higher than reported by the solar designer. Pre-feasibility assessment tools are essential to overcome the certainty gap between end users and solar designers, thus enhancing the possibility of implementing solar heating systems in various commercial and industrial processes.

Design rules for Background Oriented Schlieren experiments with least-squares based displacement calculation

Background Oriented Schlieren (BOS) is a non-intrusive optical method used to visualize density variations in fluids. A camera is used to measure the distortion of a background image displaying a random pattern due to the refraction of the light induced by the local gradients in the refractive index of the under study. In contrast to conventional schlieren, for which direct observation is possible, the images obtained with the BOS technique have to be processed. In this contribution, a computationally affordable approach based on linear least-squares minimization and adapted from optical flow techniques is presented in detail and tested in the context of BOS with the Matlab GUI application comBOS. A series of synthetic images are first analyzed to devise design rules for the definition of an optimal random Gaussian dot background pattern. Tests are performed for comBOS, the commercial BOS module included in DaVis 10, and the free PIV tool PIVlab. It is found that the diameter of the dot images on the camera sensor should be at least 3 pixels, but can be larger without affecting the accuracy of the measurement with comBOS and DaVis 10, while PIVlab severely degrades the quality of the results for dots larger than 5 pixels. The contrast and the density of dots must also be sufficient such that a minimum of 75 % of the surface of the background is shaded. If these conditions are met, the maximum systematic error in the measured distortions is 0.006 pixel for comBOS and 0.001 pixel with DaVis 10 when local gradients are small. Similar errors are found with PIVlab for dots smaller than 5 pixels in diameter, but they increase rapidly for larger dots. The random error is typically smaller than 0.004 pixel in optimal conditions, but it increases significantly for images affected by a random noise or local gradients of the distortion. Finally, it is concluded with a realistic test case that both comBOS and DaVis 10 are well suited to capture the main features of a complex compressible flow with Schlieren imaging. Thus, the main advantage of comBOS is its affordability and robustness for researchers and educators willing to implement BOS, for example in educational contexts.

NORMSEQ: a tool for evaluation, selectionand visualization of RNA-Seq normalization methods.

RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A critical step, especially in large and low input datasets or studies, is data normalization, which aims at eliminating the variability in data that is not related to biology. Many normalization methods have been developed, each of them relying on different assumptions, making the selection of the appropriate normalization strategy key to preserve biological information. To address this, we developed NormSeq, a free web-server tool to systematically assess the performance of normalization methods in a given dataset. A key feature of NormSeq is the implementation of information gain to guide the selection of the best normalization method, which is crucial to eliminate or at least reduce non-biological variability. Altogether, NormSeq provides an easy-to-use platform to explore different aspects of gene expression data with a special focus on data normalization to help researchers, even without bioinformatics expertise, to obtain reliable biological inference from their data. NormSeq is freely available at: https://arn.ugr.es/normSeq.

Hybrid DFM – Petri net approach for dynamic reliability analysis of smart transmitters

AbstractSmart transmitters are increasingly being deployed in safety critical systems. Although the processing and diagnostic features provided by digital systems are advantageous, it introduces additional complexity in reliability modelling of systems. The conventional Fault Tree Analysis (FTA) method for system reliability analysis has its shortcomings in modelling digital systems, to incorporate its dynamic system interaction and failure modes in detail. This is because some of the failure modes may arise due to the dynamic interactions between the modules of the system. Dynamic Flowgraph Methodology (DFM) was identified as one of the optimistic approaches to handle these interactions. DFM approach combines multi‐valued logic modelling and analysis capabilities to handle systems consisting of components that have multiple degraded states and exhibit dynamic behaviour. However, only few DFM tools have been developed and some of them are not available in public domain. The DFM approach relies heavily on development and implementation of its decision tables. The logic information present within the decision tables can be meticulously implemented using Petri Nets. Also, there are plenty of free Petri Nets tools available online. Thus, the idea of DFM was used in this work to capture the dynamic interactions by developing decision tables. The decision tables were transformed into the Petri Net models to perform the analysis. The paper demonstrates the potential of the hybrid DFM – Petri Net approach for dynamic reliability analysis of smart transmitter.

TTS package: Computational tools for the application of the Time Temperature Superposition principle

The TTS package has been developed in R software to predict the mechanical properties of viscoelastic materials, at short and long observation times/frequencies by applying the Time Temperature Superposition (TTS) principle. TTS is a physical principle used in material science to estimate mechanical properties beyond the experimental range of observed times/frequencies by shifting data curves obtained at other temperatures relative to a reference temperature in the dataset. It is a methodology related to accelerated life-tests and reliability, whereas the TTS library is one of the first open source computational tool to apply the TTS principle. This R package provides free computational tools to obtain master curves that characterize materials from a thermal-mechanical approach. The TTS package also proposes, implements and explains our own method to obtain the shift factors and the master curve in a TTS analysis, based on horizontal shifting of the first derivative function of viscoelastic properties. This procedure provides shift factors estimates and smooth master curve estimates using B-spline fitting, in a fully automatic way, without assuming any parametric expression. Williams-Landel-Ferry (WLF) and Arrhenius TTS parametric models are also implemented in the TTS package. They can be fitted from shifts obtained by the our first derivative based method.

A Methodology to Plan Wireless Network in Indonesian Rural Areas

Wireless telecommunication networks have been widely implemented in Indonesia. However, the planning methodology hasn’t been intensively studied. In this paper, we proposed a novel methodology for wireless local area network planning in Indonesian rural area. Our proposed method consists of eleven steps of work emphasizes the ease of implementation, market survey consideration, Indonesian Government standard application, and free tools usage optimization. At the end, an example of a network design created by following the proposed methodology for Sebira Island is presented.

Introduction to Qualitative Data Analysis and Coding with QualCoder

<i>This article demonstrates the process of coding textual data, using QualCoder, a free and open-source software tool for supporting the qualitative data analysis process. The aim is to introduce novice qualitative researchers and undergraduate students of qualitative methods to the process of open coding in a clear and concise way. The systematic coding of the empirical data is a crucial first step in many popular qualitative methods like Thematic Analysis or Interpretative Phenomenological Analysis. The initial coding phase is a prerequisite for analyzing and making sense of the data. By using QualCoder, the researcher utilizes a dependable, efficient, and easily accessible tool to work with coding without losing transparency, rigor, and depth in the process. The article concludes by discussing the multiple benefits of using such a tool for the coding process, as well as limitations and potential risks, and thus highlighting the multi-purpose pairing between technology and qualitative research.</i>