Open Source Software Applications Research Articles

INFORMATION SYSTEM DEVELOPMENT FOR WATER TREATMENT TECHNOLOGY IN DISTRICT PANDEGLANG USING OPEN SOURCE SOFTWARE (OSS)

Clean water needs in almost all regions in Indonesia became a very important thing nowadays, although the areas not experiencing drought. This is due to existing water is no longer eligible for use as daily life water. In some areas the water have been polluted and certain natural conditions make it difficult for population to get their water. Pandeglang district is one of disadvantaged areas that experiencing problems of clean water needs, although this area has water resources are abundant. To help residents in solving this problem, it will be required an information of water treatment technology that can be widely accessed by residents in the Pandeglang district. By using opensource software applications, the information system for water treatment technology can be developed to provide information of appropriate technology needs for solving the problem of providing clean water in Pandeglang.keywords : information system for technology, clean water management, waste water treatment, environmental technology, hypertext document, free open sourcesoftware (OSS).

QPhenoMetrics: An open source software application to assess vegetation phenology metrics

Phenology is one of the most reliable indicators of vegetation dynamics. Assessing and monitoring the dynamics of phenology is relevant to support several decisions in order to improve the efficiency of several farming practices. An open source application – QPhenoMetrics - implemented in QGIS software that estimates vegetation phenology metrics is presented, using Earth Observation Systems (EOS) based time-series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) as proxies for phenology. QPhenoMetrics is characterized by freely-usable and updatable code, acceptance of satellite images or text formats, time-series analysis toolbox allowing the selection of region of interest with statistical quality assessment for Vegetation Indices (VI), and estimation of ensemble metrics. The application is structured in three components: (i) input data; (ii) pre-processing of the VI time-series and several fitting methods and (iii) computation of the phenological metrics. QPhenoMetrics produces a plot with the VI time-series and corresponding phenology metrics, and a spreadsheet is created with a list of NDVI or EVI values estimated using the selected fitting method. To evaluate the application, two main Portuguese crops, vineyards and maize, and MOD13 data from MODIS sensor during 2011–2012 were considered. QPhenoMetrics was validated with vineyard phenology observations (2007–2011). A comparative analysis with software products TimeSat and Spirits was also performed. It was concluded that QPhenoMetrics can be very useful for common users to extract phenology information for 16 daily MODIS data in HDF format, text files with NDVI/EVI data and ASCII files, through a simple and intuitive graphic interface. Furthermore, the user can evaluate the quality assessment of VI of the images used. QPhenoMetrics is an effective open source tool that in addition to being free, is readily modifiable by user according to the study requirements.

Determinants of adoption for open-source office applications: A plural investigation

ABSTRACTThis article focuses on the determinants influencing organizational adoption of vendor-supported open-source software applications or open-source office applications (OSOAs). We employed a plural investigation with QUAL/QUAN sequence. Empirical analysis of the data obtained from 257 IT managers identified various technological, organizational, and environmental determinants that influence the OSOA adoption either positively or negatively. These findings offer valuable insights for IT managers and OSOA vendors which can guide them in formulating appropriate strategies for OSOA adoption.

Advantages and Disadvantages in Image Processing with Free Software in Radiology.

Currently, there are sophisticated applications that make it possible to visualize medical images and even to manipulate them. These software applications are of great interest, both from a teaching and a radiological perspective. In addition, some of these applications are known as Free Open Source Software because they are free and the source code is freely available, and therefore it can be easily obtained even on personal computers. Two examples of free open source software are Osirix Lite® and 3D Slicer®. However, this last group of free applications have limitations in its use. For the radiological field, manipulating and post-processing images is increasingly important. Consequently, sophisticated computing tools that combine software and hardware to process medical images are needed. In radiology, graphic workstations allow their users to process, review, analyse, communicate and exchange multidimensional digital images acquired with different image-capturing radiological devices. These radiological devices are basically CT (Computerised Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), etc. Nevertheless, the programs included in these workstations have a high cost which always depends on the software provider and is always subject to its norms and requirements. With this study, we aim to present the advantages and disadvantages of these radiological image visualization systems in the advanced management of radiological studies. We will compare the features of the VITREA2® and AW VolumeShare 5® radiology workstation with free open source software applications like OsiriX® and 3D Slicer®, with examples from specific studies.

An introduction to face-recognition methods and its implementation in software applications

Face detection and recognition technology has shown a steep development in the field of scientific research and is subsequently harvesting growing interest from the industry, which in fact can be confirmed seeing numerous implementations in forms of commercial applications such as autofocus in digital cameras, human computer interfaces in smartphones, or even video surveillance cameras in airports. In response to this growing interest and willingness to implement this technology of face detection and face recognition technology, this paper will provide the readers with fundamental knowledge of how face detection essentially works and ought to help the readers to establish a foothold in developing own ideas using face detection technology. The main purpose of this research paper is to introduce several significant principles of current face-detecting methods such as active shape model (ASM), active appearance model (AAM) and constrained local models (CLM) in a comprehensive manner and to provide some insight on closely related topics such as principal component analysis and eigenfaces. In this paper, we will also present selected examples of implementations of above mentioned face-detecting methods via open-source software applications such as of xFacetracker and FaceSubstitution with openFrameworks.

An introduction to face-recognition methods and its implementation in software applications

Face detection and recognition technology has shown a steep development in the field of scientific research and is subsequently harvesting growing interest from the industry, which in fact can be confirmed seeing numerous implementations in forms of commercial applications such as autofocus in digital cameras, human computer interfaces in smartphones, or even video surveillance cameras in airports. In response to this growing interest and willingness to implement this technology of face detection and face recognition technology, this paper will provide the readers with fundamental knowledge of how face detection essentially works and ought to help the readers to establish a foothold in developing own ideas using face detection technology. The main purpose of this research paper is to introduce several significant principles of current face-detecting methods such as active shape model (ASM), active appearance model (AAM) and constrained local models (CLM) in a comprehensive manner and to provide some insight on closely related topics such as principal component analysis and eigenfaces. In this paper, we will also present selected examples of implementations of above mentioned face-detecting methods via open-source software applications such as of xFacetracker and FaceSubstitution with openFrameworks.

Awareness and Adoption of Open Source Software among Library and Information Science Professionals of Engineering Colleges of Karnataka: A Survey

Today, Information and Communication Technology has provided us with an ability of flexibility and access to information and resources (Agarwal, Manjari, 2014). It has empowered the Library and Information Science community to adapt to the new open source software (OSS) tools and technologies in their day-to-day activities in their libraries. Development of OSS based on the sharing and collaborative improvement of software source code has a history that is essentially as long as software development itself. Open source initiative was formed in 1998 as an educational, advocacy and stewardship organisation at an important moment in the history of OSS and collaborative development. This study is aimed to study the different OSS of library digitisation in engineering college libraries of Karnataka, to Study the nature and type of open source digital library software used in engineering college libraries of Karnataka and to Study the areas of application of OSS in engineering college libraries of Karnataka. The investigation has conducted a survey among 147 engineering college librarians in the state of Karnataka on the above matters. The results are discussed under the categories such as status of library automation and digitisation, use of automation and digital library software, management of IT and network requirement of library, own digital library/institutional repository software, involvement in installation of OSS, involvement in installation of OSS, potential areas of adopting OSS in library and duration of OSS implementation in library.

Application of open-source software for industrial problems of vehicle lift-off gas dynamics

High-power shock, heat, mechanical and especially acoustic loads present a serious problem as their impact on the rocket and the launch pad can be too strong. Turbulent supersonic jets ejected from the vehicle nozzles are the main source of these loads. One way to reduce the intensity of acoustic loads is to supply a special system of water jets that interact with the supersonic gas jets near the rocket nozzles. Numerical simulation of this interaction is an important part of the design of such noise reduction systems. The proposed numerical model should enable simulation of various processes of different scale, such as gas/droplets interaction, nozzle jets in the near field, acoustic loads in the far field, chemical reactions and others. Therefore, such a model should be modular and hierarchically aligned. A flexible and extensible implementation of the numerical model can be possible with open-source codes. This paper concerns the problem of numerical simulation of compressible turbulent supersonic jets. The hybrid gas dynamics solver which was used in this investigation is one of the main modules of the general numerical model. Preliminary results of verification of this module are presented. Comparison of numerical and experimental results for various experimental cases, both Russian and foreign, is given.

X-Ray Computed Tomography of Crop Plant Root Systems Grown in Soil.

Non-destructive methods to quantify the root system architecture of a plant grown in soil are essential to aid our understanding of the factors that impact plant root development in natural environments. With environmental change threatening our ability to sustain agricultural productivity for an expanding global population, the application of these methods has never before seen such an increase in demand. X-ray computed tomography (CT) based phenotyping techniques permit the spatio-temporal quantification of roots, helping to identify novel adaptive root architectural responses to abiotic and biotic factors. This protocol reports an integrated workflow from column preparation and plant growth to image and quantification of the root system using novel open source software applications, RooTrak and RooTh. © 2017 by John Wiley & Sons, Inc.

Automatic approval prediction for software enhancement requests

Software applications often receive a large number of enhancement requests that suggest developers to fulfill additional functions. Such requests are usually checked manually by the developers, which is time consuming and tedious. Consequently, an approach that can automatically predict whether a new enhancement report will be approved is beneficial for both the developers and enhancement suggesters. With the approach, according to their available time, the developers can rank the reports and thus limit the number of reports to evaluate from large collection of low quality enhancement requests that are unlikely to be approved. The approach can help developers respond to the useful requests more quickly. To this end, we propose a multinomial naive Bayes based approach to automatically predict whether a new enhancement report is likely to be approved or rejected. We acquire the enhancement reports of open-source software applications from Bugzilla for evaluation. Each report is preprocessed and modeled as a vector. Using these vectors with their corresponding approval status, we train a Bayes based classifier. The trained classifier predicts approval or rejection of the new enhancement reports. We apply different machine learning and neural network algorithms, and it turns out that the multinomial naive Bayes classifier yields the highest accuracy with the given dataset. The proposed approach is evaluated with 40,000 enhancement reports from 35 open source applications. The results of tenfold cross validation suggest that the average accuracy is up to 89.25%.

P06.05: Automation of the fetal right myocardial performance index (RMPI) to optimise repeatability

To compare the repeatability of an automated fetal right myocardial performance index (MPI) algorithm with manual measurements and to evaluate the degree of absolute agreement between values. A secondary aim is to determine the impact of MPI observer experience on these two aspects. A prospective cross-sectional study. Spectral Doppler double waveform, right MPI images were acquired, using a Voluson E8 from 65 uncomplicated singleton pregnancies at 22–39 weeks gestation. Three clearest cardiac cycles were selected from each case, by an experienced operator. Exported raw format images were analysed first with a MATLAB automated MPI software and then independently by an experienced and an inexperienced observer. Intraclass correlation coefficients (ICCs) and 95% confidence intervals (95% CI) were used to evaluate manual and automated intra- and inter-observer repeatability. Absolute agreement between the manual and corresponding automated MPI values was evaluated using ICCs, 95% CI and Bland-Altman plots. Successful automation was performed on 63 cases (97%) showing repeatability ICCs of: 0.83 for manual intra-observer; 0.77 for manual inter-observer and 1.00 for automated repeatability. The degree of absolute agreement between manual and automated values was: inexperienced observer ICC 0.43 (95% CI 0.21–0.62); experienced observer ICC 0.76 (95% CI 0.63–0.85). Right MPI may be a potentially useful tool in the early detection of cardiac dysfunction in a range of pathologies. Automation is precise, sensitive, demonstrates a superior reproducibility over manual measurements and reduces the experience required for successful analysis. This may lend a greater clinical applicability to MPI in functional fetal echocardiography, and future studies to develop a universal reference range based on automation would be useful. We aim for this, along with our Left MPI algorithm, to be made available as an open-source software application to apply to images from any ultrasound machine.

EPICS device support for an ATCA CDAQ Board with hot-plug capabilities

The Advanced Telecommunications Computing Architecture (ATCA) standard defines a high performance technical solution that meets the requirements for fast controllers on large-scale physics experiments like ITER. This platform provides high throughput, scalability and features for high availability such as redundancy and intelligent platform management which are essential for steady state experiments.An ATCA Control and Data Acquisition (CDAQ) demonstration system was developed for the ITER Fast Plant System Controller (FPSC) project, which is already available in the ITER Catalog. This system comprises a board with 48 galvanic isolated analog and/or digital channels configurable as input or output with digital signal processing capabilities performed by a Field Programmable Gate Array (FPGA) and an ATCA carrier.The Experimental Physics and Industrial Control System (EPICS) is a set of open source software tools, libraries and applications used worldwide to create distributed soft real-time control systems for scientific instruments. To provide the hardware integration on the EPICS environment, a device support has been developed as a software layer, which is comparable to the abstraction layer provided by the device driver on the Operating Systems.This paper presents the implementation and test of an EPICS Device Support for the ATCA CDAQ Board that comprises templates for easy configuration of the entire system. This solution also allows simultaneous and independent acquisition by each board, providing hot-plug features which support insertion and removal of boards while keeping other modules and the overall system running.Operation with several boards and different versions of Linux operating system was performed and the results are presented.

Reliability analysis for multi-release open-source software systems with change point and exponentiated Weibull fault reduction factor

Evolutions in technology and rapid growth of open-source software (OSS) applications have made upgradation indispensable. To incorporate vagaries in users needs and environmental situations that affect the reliability growth of OSS, fault reduction factor (FRF) is one of the important factors to be considered during multi-release software development process. In this paper, a software reliability growth model (SRGM) has been proposed for successive releases to include some of the critical but realistic characteristics such as time variant FRF, effect of change point due to changing strategies and error generation during fault removal phenomena. For model validation, two popular open-source projects—Mozilla and Gnome—have been chosen for its multi-release real data sets. An optimal updation schedule problem is formulated, and a numerical illustration has been worked out. The goodness of fit of the proposed model is shown by comparing it with one of the well-known models reported in the literature.

Development of Algorithm for Lorenz Equation through the Application of Open Source Software

Physiological system is dynamic and has a multi-factorial influence; hence, nonlinear and complex in nature. Due to limitation in data capturing in discreet time points, the general trend is that majority of physiological researches are approached with linearity; and hence problems of complexity are solved in an empirical manner. However, in recent time there is an increasing trend to understand the physiological system in a quantitative manner across the globe. Due to unavailability of costly software, students are unexposed to this global trend. In physical system complexity was first addressed by Edward Lorenz in 1963, which is now known as Lorenz equation. Here we depict the simple computational approach to represent such complexity of the Lorenz equation through some freely available open source software’s, so that students by themselves can appreciate the importance of quantification in an understanding of the complex behaviour of a nonlinear dynamical system.

Development of an Optical Object Detection Solution for Defect Prevention in a Learning Factory

This article investigates a potential application of low cost computer hardware and open source software in machining areas of Learning Factories. Based on the implementation of an optical object detection to discover human errors in the setup process of a milling machine, the paper presents an example of how value stream improvements in Learning Factories can be achieved by student projects.Therefore, the process of identifying possible solutions which are suitable for solving a problem in the value stream of a Learning Factory is described. In the presented case, this is an IT-solution to establish a Poka-Yoke system for depositing a work piece in a milling machine correctly. A solution, which uses a Raspberry Pi, is developed and integrated in the process. Furthermore, the ability of low cost hardware components and simple algorithms resting upon freely available software libraries to fulfil the requirements of modern manufacturing is demonstrated. Finally, this study illustrates that the implementation of in-house low cost digitalization rather rests on a profound understanding of the affected manufacturing process than on previous knowledge of programming or electronics.

A Comparison Among ARIMA, BP-NN, and MOGA-NN for Software Clone Evolution Prediction

Software evolution continues throughout the life cycle of the software. During the evolution of software system, it has been observed that the developers have a tendency to copy the modules completely or partially and modify them. This practice gives rise to identical or very similar code fragments called software clones. This paper examines the evolution of clone components by using advanced time series analysis. In the first phase, software clone components are extracted from the source repository of the software application by using the abstract syntax tree approach. Then, the evolution of software clone components is analyzed. In this paper, three models, Autoregressive Integrated Moving Average, back propagation neural network, and multi-objective genetic algorithm-based neural network, have been compared for the prediction of the evolution of software clone components. Evaluation is performed on the large open-source software application, ArgoUML. The ability to predict the clones helps the software developer to reduce the effort during software maintenance activities.

Coherence of comments and method implementations: a dataset and an empirical investigation

In this paper, we present the results of a manual assessment on the coherence between the comments and the implementation of 3636 methods in three open source software applications (for one of these applications, we considered two different subsequent versions) implemented in Java. The results of this assessment have been collected in a dataset we made publicly available on the Web. The creation of this dataset is based on a protocol that is detailed in this paper. We present that protocol to let researchers evaluate the goodness of our dataset and to ease its future possible extensions. Another contribution of this paper consists in preliminarily investigating on the effectiveness of adopting a Vector Space Model (VSM) with the tf-idf schema to discriminate coherent and non-coherent methods. We observed that the lexical similarity alone is not sufficient for this distinction, while encouraging results have been obtained by applying an Support Vector Machine (SVM) classifier on the whole vector space.

Rationale and design of mDOT-HuA study: a randomized trial to assess the effect of mobile-directly observed therapy on adherence to hydroxyurea in adults with sickle cell anemia in Tanzania.

BackgroundHydroxyurea (HU) has been demonstrated to be efficacious in reducing complications in individuals with sickle cell anemia (SCA) but poor adherence is a barrier. Directly Observed Therapy (DOT) has been shown to improve adherence in various chronic diseases but there is limited data in adults with SCA.Methods and designTo examine the effect of mobile-directly observed therapy (mDOT) on adherence to HU (mDOT-HuA) in adults with SCA at Muhimbili National Hospital in Tanzania. The mDOT-HuA study is a single centre, prospective, randomized, open label clinical trial. One-hundred individuals with SCA with haemoglobin SS genotype, aged ≥18 years, living in Dar es Salaam, able and willing to record and submit videos electronically will be included. Participants will be divided into two treatment arms; 50 in the standard monitoring (SM) arm will receive mobile phones and fixed dose HU therapy with standard monitoring; 50 in the mDOT arm will receive mobile phones, fixed dose HU therapy with standard monitoring and a mobile directly observed web based medication adherence monitoring system. The primary outcome is the proportion of participants achieving ≥80 % HU adherence compared between the two arms as assessed through medication possession ratio at the end of 3 months of treatment. REDCap, an open source software application will be used to collect data using clinical research forms. The proportions of adherence in the two arms will be compared by Fisher’s exact test. Analysis of outcomes will have performed by both the intention-to treat and per-protocol methods.DiscussionShould this study become sucessful, it will have the potential for the development of novel strategies for improving HU adherence in SCA.Trial registrationClinicalTrials.gov Identifier: NCT02844673, registered on 25tht July 2016 (retrospectively registered).

A framework to embed a spatial statistics toolbox in open-source GIS software: kernel density estimation example

It is widely known that geographic information systems (GIS) should include more spatial data analysis (SDA) techniques. The issues of which techniques should be included and how statistical analysis can be integrated with GIS are still widely debated. This paper focuses on the development of a framework that implements R SDA techniques in the uDig. For this purpose, a simple interface is designed between two open-source software applications, uDig and the R statistical software package. The tight coupling strategy is adopted with the RCaller interpreter. Overall, the integration is successfully implemented and tested by users and developers. Fourteen geospatial and four non-geospatial techniques are integrated into uDig successfully, which demonstrates the success of the proposed framework. Among these techniques, the kernel density estimation (KDE) technique is explained with a sample data set to show every step of the implementation. The user tests also prove the success of the integration.

Mapping social vulnerability to natural hazards in Italy: A suitable tool for risk mitigation strategies

Italy is one of the European countries that are most heavily exposed to a wide range of natural hazards, which might cause large economic losses. In this context, the assessment of social vulnerability has an important role for evaluating the capacity of a community to prepare for, respond to and recover from disasters. However there are currently no published studies analysing social vulnerability and its spatial distribution in Italy. Within this framework, this paper aims to apply a proven method for assessing social vulnerability at the national scale, while considering the contribution of the socioeconomic and demographic factors that affect the Italian population. The proposed methodology is based on the Hazard-of-Place Model approach, and uses free and open source software applications (FOSS). Specifically, we selected significant components through Principal Component Analysis and derived their spatial distribution. Using component scores, we derived a social vulnerability index, evaluated its geographic distribution, and performed a cluster analysis on its spatial variation. The analysis identified different spatial patterns across Italy, providing useful information for identifying the communities most likely to experience negative natural disaster impacts due to their socioeconomic and demographic characteristics. This research represents an important contribution to improve the potentiality of risk mitigation strategies and in designing risk custom-made policies.