Proprietary Software Packages Research Articles

A method for automated masking and plantar pressure analysis using segmented computed tomography scans

BackgroundPlantar pressure, a common gait and foot biomechanics measurement, is typically analyzed using proprietary commercial software packages. Regional plantar pressure analysis is often reported in terms of underlying bony geometry, and recent advances in image processing and accessibility have made computed tomography, radiographs, magnetic resonance imaging, or other imaging methods more popular for incorporating bone analyses in biomechanics. Research QuestionCan a computed tomography-based regional mask provide comparable regional analysis to commercial plantar pressure software and can the increased flexibility of an in-house method obtain additional insight from common measurements? MethodsA plantar pressure analysis method was developed based on bony geometry from computed tomography scans to calculate peak pressure, pressure time integral incorporating sub-peak values, force time integral, pressure gradient, and pressure gradient angle. Static and dynamic plantar pressure were acquired for 4 subjects (male, 65 ± 2.4 years). Plantar pressure variables were calculated using commercial and computed tomography-based systems. ResultsDynamic peak pressure, pressure time integral, and force-time integral computed using the bone-based software was 5% (9kPa), 7% (0.3kPa-s) and 13% (0.3 N-s) different than the and commercial software on average. Region masks of the metatarsals and toes differed between commercial and computed tomography-based software due to subject-specific bone geometry and toe shape. Pressure time integral values incorporating sub-peak pressure were higher and demonstrated higher relative hindfoot values compared to those without. Removing step-on frames to static pressure analysis decreased forefoot pressures. Regional maps of peak pressure and maximum pressure gradient demonstrate different peak locations. SignificanceComputed tomography-based regional masks are comparable to commercial masks. Inclusion of static step-on frames and sub-peak pressures may change regional plantar pressure patterns. Differences in location of maximum pressure gradient and peak pressure may be useful for assessing subject specific injury risk.

Examining the Optimal Choice of SEM Statistical Software Packages for Sustainable Mathematics Education: A Systematic Review

Intending to analyze structural relationships between measured variables and latent constructs, researchers tend to adopt structural equation modeling (SEM) through either “covariance-based SEM” (CB-SEM) or “variance-based SEM” (VB-SEM)/“partial least squares SEM” (PLS-SEM) by using numerous statistical applications. Nevertheless, the reviews on understanding the optimal choice of proprietary statistical software packages in SEM approaches are scarce despite its immense importance in sustaining education. Therefore, a systematic review would be obligated to scrutinize the empirical studies to fill this gap. By employing the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, a total of 47 publications that met the inclusion criteria were obtained. To extract articles from August 2018 to 2022, Scopus, Web of Science (WoS), and The Education Resources Information Center (ERIC) databases were adopted. The findings imply that six types of proprietary statistical software packages emerged as an optimal choice: Lisrel, Amos, Mplus, SmartPLS, R package (plspm), and WarpPLS. Despite the widespread usage of a variety of statistical applications, SmartPLS and AMOS were rigorously utilized in VB-SEM/PLS-SEM and CB-SEM, respectively. This review is important for practitioners to discover which statistical tools are relevant to use and to identify gaps in order to sustain mathematics education for the future.

PIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides

The isoelectric point (pI) is a fundamental physicochemical property of peptides and proteins. It is widely used to steer design away from low solubility and aggregation and guide peptide separation and purification. Experimental measurements of pI can be replaced by calculations knowing the ionizable groups of peptides and their corresponding pKa values. Different pKa sets are published in the literature for natural amino acids, however, they are insufficient to describe synthetically modified peptides, complex peptides of natural origin, and peptides conjugated with structures of other modalities. Noncanonical modifications (nCAAs) are ignored in the conventional sequence-based pI calculations, therefore producing large errors in their pI predictions. In this work, we describe a pI calculation method that uses the chemical structure as an input, automatically identifies ionizable groups of nCAAs and other fragments, and performs pKa predictions for them. The method is validated on a curated set of experimental measures on 29 modified and 119093 natural peptides, providing an improvement of R2 from 0.74 to 0.95 and 0.96 against the conventional sequence-based approach for modified peptides for the two studied pKa prediction tools, ACDlabs and pKaMatcher, correspondingly. The method is available in the form of an open source Python library at https://github.com/AstraZeneca/peptide-tools, which can be integrated into other proprietary and free software packages. We anticipate that the pI calculation tool may facilitate optimization and purification activities across various application domains of peptides, including the development of biopharmaceuticals.

Joining Constraint Satisfaction Problems and Configurable CAD Product Models: A Step-by-Step Implementation Guide

In configuration design, the task is to compose a system out of a set of predefined, modu-lar building blocks assembled by defined interfaces. Product configuration systems, both with or without integration of geometric models, implement reasoning techniques to model and explore the resulting solution spaces. Among others, the formulation of constraint satisfaction problems (CSP) is state of the art and the informational background in many proprietary configuration engine software packages. Basically, configuration design tasks can also be implemented in modern computer aided design (CAD) systems as these contain different techniques for knowledge-based product modeling but literature reports only little about detailed application examples, best practices or training materials. This article aims at bridging this gap and presents a step-by-step implementation guide for CSP-based CAD configurators for combinatorial designs with the example of Autodesk Inventor.

Does possessing an installed base induce a proprietary software producer to act aggressively or mildly in pricing and intrinsic quality provision?

AbstractThis paper investigates competition between open‐source software (OSS) and proprietary software (PS) which possesses an installed base. We find that an increase in PS installed base does not necessarily induce the PS producer to increase price or reduce intrinsic quality. Specifically, if OSS is weakly (moderately) compatible with PS, then an increase in PS installed base induces the PS producer to invest less (more) in intrinsic quality. Regarding the price of PS, if OSS is highly compatible with PS possessing a large installed base, then an increase in installed base induces the PS producer to sell products for a lower price.

Computer Flow Simulation and Verification for Turbine Blade Channel Formed by the C-90-22 A Profile

Currently, software products for numerical simulation of fluid dynamics processes (Ansys, Star CCM+, Comsol) are widely used in the power engineering industry when designing new equipment. However, computer simulation methods embedded in proprietary software products make specialists choose grid settings, boundary conditions, and a solver providing the minimal deviation from experimental data with the maximal calculation speed. This paper analyzes the influence of the main grid settings and boundary conditions in the Ansys software package on the error in the computer simulation of flows in standard elements of power equipment and gives recommendations for their optimal choice. As standard elements were considered blade turbine channels formed by C-90-22 A profiles.

A Customized Data Model for an Integrated Process of Requirements and Configuration Management

This work aims to propose a customized, open-source data model for supporting an integrated process of Requirements and Configuration Management that allows for keeping track of which requirement originated each part, subsystem and system—and vice versa—, over their entire life cycle. That model might prospectively contribute to the processes of Aeronautical Engineering design and Continued Airworthiness in organizations that do not want either to invest in complex existing commercial, proprietary software packages or to train their professionals for that purpose. The complete source code of the model is provided in Python and SQL languages.

A geospatial database management system for the collection of medicinal plants.

Medicinal plants are increasingly used, both for medical applications and personal healthcare. However, existing herbal database systems for plant retrieval offer only basic information and do not support real-time analysis of the spatial aspects of plantations and distribution sites. Moreover, data records are usually static and not publicly available as they rely on costly proprietary software packages. To address these shortcomings, including limiting the time needed for collection and data processing, a novel medicinal plants geospatial database management system is proposed. The system allows localization of plant sites and data presentation on an interactive heat map displaying spatial information of plants selected by the user within a specific radius from the user's location, including automatic presentation of an itinerary giving the optimal route between user location and plant destinations selected. The approach relies on dynamic and role-based data management, an interactive map that includes graphics and integrated geospatial analyses thanks to cross-platform, geographical a JavaScript library and Google API. Both spatial data and attributes are available in real time. The system would support effective collaboration, among herb farmers, government agencies, private investors, healthcare professionals and the general public with regard to various aspects of medicinal plants and their applications.

Development of textual analytics tools for analysis of public and specialized sources in the tasks of foresight and system analysis

A combined approach to extracting concepts and constructing classifiers and ontologies using open and proprietary software packages has been developed. Modern approaches, methods and models of storing large amounts of poorly structured information from Open Source software sets are studied. An ontology was built, in the leaves of which a classifier based on Boolean rules was implemented using SAS(R) Content Categorization Software. To build the ontology, the approach of constructing vectors of related concepts is employed using the Open Source library of Gensim software, namely the Word2Vec model. A typical algorithm for constructing a classifying ontology has been developed. The results of the research can be used to build an ontology of subject areas, create classification ontologies and mark corpora of texts.

An educational software suite for comprehensive learning of Computer‐Aided Engineering

AbstractThe learning of Computer‐Aided Engineering (CAE) usually involves practical computer lessons on the use of CAE software. Software packages suitable for learning should be user‐friendly and accessible, with an affordable cost. However, the CAE freeware and proprietary software available in the market are relatively difficult to use for novices. Furthermore, most proprietary software packages are very costly, hindering the access of learners. In this study, a CAE freeware suite, CAE 3D, has been developed for supporting the learning of CAE technology. CAE 3D contains four modules for analyzing 3D solid mechanics, heat transfer, and mechanical vibration problems by the finite element method, and 3D fluid dynamics problems by the finite volume method. Unlike most CAE freeware applications, the user interface of CAE 3D is a purely graphical user interface instead of containing some text‐based user interfaces. As CAE 3D is user‐friendly and capable of analyzing various types of engineering problems, it is suitable for use as a learning tool of CAE. For example, learners can adjust parameters, such as geometry, material properties, and/or boundary conditions, to explore the effects of a given setting on the CAE results. This article explains the CAE learning process, development of CAE 3D software and application of CAE 3D to university classrooms. The classroom feedback indicates that the students were highly satisfied with CAE 3D in terms of the usability, the reliability of results and the contribution toward learning. These responses support the applicability of CAE 3D in CAE education.

Quantum GIS (QGIS): An introduction to a free alternative to more costly GIS platforms

Geographic information system (GIS) software packages can be prohibitively expensive, causing many to shy away from mapping and spatial analysis. This 7-page fact sheet written by Jeffry M. Flenniken, Steven Stuglik, and Basil V. Iannone III and published by the UF/IFAS School of Forest Resources and Conservation introduces the reader to a free GIS software package called Quantum GIS (QGIS), walking the reader through simple GIS processes that can be used to visualize spatial patterns of importance to a variety of fields, including natural resources, agriculture, and urban planning. Learn how to create a land-cover map for a county of interest and create heatmaps that illustrate the density of a given attribute (Florida Springs for this example). This publication will benefit those interested in incorporating GIS into their work but who are unable to afford expensive proprietary GIS software packages, as well as anyone interested in learning a new GIS software package. https://edis.ifas.ufl.edu/fr428

ACTman: Automated preprocessing and analysis of actigraphy data

ObjectivesTo introduce a novel software-library called Actigraphy Manager (ACTman) which automates labor-intensive actigraphy data preprocessing and analyses steps while improving transparency, reproducibility, and scalability over software suites traditionally used in actigraphy research practice. DesignDescriptive. MethodsUse cases are described for performing a common actigraphy task in ACTman and alternative actigraphy software. Important inefficiencies in actigraphy workflow are identified and their consequences are described. We explain how these hinder the feasibility of conducting studies with large groups of athletes and/or longer data collection periods. Thereafter, the information flow through the ACTman software is described and we explain how it alleviates aforementioned inefficiencies. Furthermore, transparency, reproducibility, and scalability issues of commonly used actigraphy software packages are discussed and compared with the ACTman package. ResultsIt is shown that from an end-user perspective ACTman offers a compact workflow as it automates many preprocessing and analysis steps that otherwise have to be performed manually. When considering transparency, reproducibility, and scalability the design of the ACTman software is found to outperform proprietary and open-source actigraphy software suites. As such, ACTman alleviates important bottlenecks within actigraphy research practice. ConclusionsACTman facilitates the current transition towards larger datasets containing data of multiple athletes by automating labor-intensive preprocessing and analyses steps within actigraphy research. Furthermore, ACTman offers many features which enhance user-convenience and analysis customization, such as moving window functionality and period selection options. ACTman is open-source and thus fully verifiable, in contrast with many proprietary software packages which remain a black box for researchers.

Open-source QSAR models for pKa prediction using multiple machine learning approaches

BackgroundThe logarithmic acid dissociation constant pKa reflects the ionization of a chemical, which affects lipophilicity, solubility, protein binding, and ability to pass through the plasma membrane. Thus, pKa affects chemical absorption, distribution, metabolism, excretion, and toxicity properties. Multiple proprietary software packages exist for the prediction of pKa, but to the best of our knowledge no free and open-source programs exist for this purpose. Using a freely available data set and three machine learning approaches, we developed open-source models for pKa prediction.MethodsThe experimental strongest acidic and strongest basic pKa values in water for 7912 chemicals were obtained from DataWarrior, a freely available software package. Chemical structures were curated and standardized for quantitative structure–activity relationship (QSAR) modeling using KNIME, and a subset comprising 79% of the initial set was used for modeling. To evaluate different approaches to modeling, several datasets were constructed based on different processing of chemical structures with acidic and/or basic pKas. Continuous molecular descriptors, binary fingerprints, and fragment counts were generated using PaDEL, and pKa prediction models were created using three machine learning methods, (1) support vector machines (SVM) combined with k-nearest neighbors (kNN), (2) extreme gradient boosting (XGB) and (3) deep neural networks (DNN).ResultsThe three methods delivered comparable performances on the training and test sets with a root-mean-squared error (RMSE) around 1.5 and a coefficient of determination (R2) around 0.80. Two commercial pKa predictors from ACD/Labs and ChemAxon were used to benchmark the three best models developed in this work, and performance of our models compared favorably to the commercial products.ConclusionsThis work provides multiple QSAR models to predict the strongest acidic and strongest basic pKas of chemicals, built using publicly available data, and provided as free and open-source software on GitHub.

SEML: A Simplified English Modeling Language for Constructing Biological Models in Julia

Many markup languages can be used to encode biological networks, each with strengths and weaknesses. Model specifications written in these languages can then used, in conjunction with proprietary software packages e.g., MATLAB, or open community alternatives, to simulate the behavior of biological systems. In this study, we present the Simplified English Modeling Language (SEML) and associated compiler, as an alternative to existing approaches. SEML supports the specification of biological reaction systems in a simple natural language like syntax. Models encoded in SEML are transformed into executable code using a compiler written in the open-source Julia programming language. The compiler performs a sequence of operations, including tokenization, syntactic and semantic error checking, to convert SEML into an intermediate representation (IR). From the intermediate representation, the compiler then generates executable code in one of three programming languages: Julia, Python or MATLAB. Currently, SEML supports both kinetic and constraint based model generation for signal transduction and metabolic modeling. In this study, we demonstrate SEML by modeling two proof-of-concept prototypical networks: a constraint-based model solved using flux balance analysis (FBA) and a kinetic model encoded as Ordinary Differential Equations (ODEs). SEML is a promising tool for encoding and sharing human-readable biological models, however it is still in its infancy. With further development, SEML has the potential to handle more unstructured natural language inputs, generate more complex models types and convert its natural language markup to currently used model interchange formats such systems biology markup language.

Performance analysis of selected hypervisors (Virtual Machine Monitors - VMMs)

Abstract Virtualization of operating systems and network infrastructure plays an important role in current IT projects. With the number of services running on different hardware resources it is easy to provide availability, security and efficiency using virtualizers. All virtualization vendors claim that their hypervisor (virtual machine monitor - VMM) is better than their competitors. In this paper we evaluate performance of different solutions: proprietary software products (Hyper-V, ESXi, OVM, VirtualBox), and open source (Xen). We are using standard benchmark tools to compare efficiency of main hardware components, i.e. CPU (nbench), NIC (netperf), storage (Filebench), memory (ramspeed). Results of each tests are presented.

Towards a methodology to build virtual reality manufacturing systems based on free open software technologies

Virtual reality and augmented reality are being increasingly used in the manufacturing field for different purposes. As a result, these technologies seem to have a very promising future in the manufacturing industry. However, most of the current applications are based on the use of expensive proprietary software packages (such as specific CAD modules). This work presents a methodology that helps programmers to build virtual and augmented reality systems, which is valid for a broad number of industrial plants. Differently to other approaches, ours is based on open technologies, most of them free of cost. The technologies proposed to build the virtual worlds are already mature at the entertainment industry. The presented approach opens new possibilities for creating virtual reality models aimed at two major directions: (1) pure simulation of real processes and products for different purposes (e.g. staff training; prototype designing; manufacturing optimization; marketing) and (2) teleoperation of real processes (e.g. in dangerous environments or in micro and macro scale manufacturing). The application of the methodology is illustrated by means of the creation of a non-immersive virtual world which represents a part-classifying station, allowing both the simulation of the real plant as well as its remote operation.

Mathematical model and algorithm of selecting software promotion options differentiated by functionality and business models

Yuriy P. Yekhlakov - Professor, Head of Department of Data Processing Automation, Tomsk State University of Control Systems and Radioelectronics (TUSUR)Address: 40, Lenina ave., Tomsk, 634050, Russian Federation.E-mail: upe@tusur.ruDmitriy N. Baraksanov - Post-graduate Student, Department of Data Processing Automation, Tomsk State University of Control Systems and Radioelectronics (TUSUR)Address: 40, Lenina ave., Tomsk, 634050, Russian Federation.E-mail: upe@tusur.ru The paper focuses on issues and tasks IT companies face with when promoting proprietary software products on consumer markets. It provides the description of the basic software product market represented as a combination of specific prospective customer groups, to which a software product line with relevant functionality can be offered using different delivery business models. The authors suggest three groups of market segment attractiveness: market attractiveness, competition level and a company’s performance in the segment. The authors developed a multi-objective mathematical model for selecting options of software product distribution in selected market segments. The following selection criteria for software distribution options in selected market segments are advanced: maximum of total profit, minimum of promotion expenses, minimum of target segments number and maximum of an integrated measure of segments attractiveness. Limitations of the model include the volume of human resources in each single-discipline group of specialists in an IT company and application of a single option of software product delivery for each of market segments. An algorithm for solution of the problem relies on successive concession method. However, suggested criteria of optimization are applicable for other methods of the multi-objective problem solution. The authors described the results of the model application for a real problem of selecting distribution options for the ‘Electronic Timetable’ software product for specialized secondary education and higher education institutions of Siberian Federal District in Russia. Twenty-four segments were selected for distribution, where two software distribution models were possible - “software as a service” (SaaS) and “application service provider” (ASP). Assessment of qualitative and quantitative parameters of the mathematical model was conducted by experts using optimistic, pessimistic and realistic scenarios. As a result of the problem solution, software product should be distributed as SaaS in 14 segments, and as ASP - in 3 segments. The results of the study may be useful for directors and managers of small IT companies when formulating strategies for proprietary software product distribution in certain target segments.

Global firms and smart technologies: IBM and the reduction of cities

The development and spread of ‘smart city’ technologies, policies and practices is now an important element of contemporary urban governance, given the role of powerful global firms such as IBM, Siemens and Cisco in their authorship. Developing a relational ontology of global ‘smart city’ firms, the paper explores the origin and development of IBM's pervasive and influential Smarter Cities strategies. The paper argues that for IBM, Smarter Cities represents an attempt to solve three strategic problems that face the firm: how to maximise its stored knowledge and ensure its labour costs deliver significant added value; how to construct new sectoral and geographic markets for this knowledge; and how to reduce, standardise and simplify the object of that knowledge – the city – as a scaleable commodity. To illustrate these issues, the paper first explores the strategic direction of IBM from being a loss‐making computer hardware manufacturer, to an information technology consultancy, identifying the role of acquisitions, city partnership, and research and development in that process. Second, it identifies how IBM has constructed a market for city or municipal services within its suite of vertical specialist markets. Third, it describes the relationship between the marketing, modelling and visualisation practices that reduce and simplify urban problems for solution through the sale of proprietary software packages, consultancy services and hardware to their clients in city government. The paper concludes by arguing that the future of smart cities is inextricably linked to the internal knowledge organisation of a small number of global technology firms.

The Impact of Open Source Software Commercialization on Firm Value

Vendors of proprietary software products are increasingly moving to business models inspired by open source software (OSS). This study investigates sources of heterogeneity in value appropriation associated with commercializing OSS. Specifically, I suggest that the relationship between a firm's OSS releases and its value depends critically on its stocks of protection mechanisms for intellectual property rights, such as software patents and software trademarks. I find that while software patent stocks positively affect the relationship between a firm's OSS product portfolio and its value, software trademark stocks have a negative effect on this relationship.

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators. Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software1 to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.