Inexpensive Software Research Articles

Highlighting bugs in software development codes using SDPET for enhancing security

The requirement for high-quality, inexpensive software that can be maintained is being driven by the rise in demand for automated online software systems. Early defect identification in SDLCs (Software Development Life Cycles) results in early adjustments and eventually on-time delivery of maintainable software, satisfying the client and fostering his trust in the development team. Many MLTs (Machine Learning Techniques) have been put out in the last ten years to increase SDP accuracy. Most of the suggested SDPs frameworks and models employ ANNs (Artificial Neural Networks), which are a popular MLTs. Software defect data are hampered by a number of problems, including duplication, correlation, feature relevance, and missing samples. However, because to the under/over fitting issues, most existing SDPs utilising ANNs have low accuracy. SDPET (Software Defect Predictions Ensemble Technique), an ensemble learning technique to produce accurate SDPs based on the AdaBoost algorithm, is proposed. The proposed schema's efficacy against RFs (Random Forests) and GBs(Gradient Boosts) for needed values through experiments. The experiment results verify that the suggested SDPET has good accuracy in training and better accuracy in test datasets when compared with other methods. The original obtained dataset was cleaned of unnecessary features, converted to csv, and is stored as dataset. csv.

A Multipathway Phosphopeptide Standard for Rapid Phosphoproteomics Assay Development

Recent advances in methodology have made phosphopeptide analysis a tractable problem for many proteomics researchers. There are now a wide variety of robust and accessible enrichment strategies to generate phosphoproteomes while free or inexpensive software tools for quantitation and site localization have simplified phosphoproteome analysis workflow tremendously. As a research group under the Association for Biomolecular Resource Facilities umbrella, the Proteomics Standards Research Group has worked to develop a multipathway phosphopeptide standard based on a mixture of heavy-labeled phosphopeptides designed to enable researchers to rapidly develop assays. This mixture contains 131 mass spectrometry vetted phosphopeptides specifically chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling networks: AMPK signaling, death and apoptosis signaling, ErbB signaling, insulin/insulin-like growth factor-1 signaling, mTOR signaling, PI3K/AKT signaling, and stress (p38/SAPK/JNK) signaling. Here, we describe a characterization of this mixture spiked into a HeLa tryptic digest stimulated with both epidermal growth factor and insulin-like growth factor-1 to activate the MAPK and PI3K/AKT/mTOR pathways. We further demonstrate a comparison of phosphoproteomic profiling of HeLa performed independently in five labs using this phosphopeptide mixture with data-independent acquisition. Despite different experimental and instrumentation processes, we found that labs could produce reproducible, harmonized datasets by reporting measurements as ratios to the standard, while intensity measurements showed lower consistency between labs even after normalization. Our results suggest that widely available, biologically relevant phosphopeptide standards can act as a quantitative "yardstick" across laboratories and sample preparations enabling experimental designs larger than a single laboratory can perform. Raw data files are publicly available in the MassIVE dataset MSV000090564.

Сертификация программного и программно-аппаратного обеспечения транспортных информационных систем в соответствии с требованиями безопасности

A number of methods, methods and tools are proposed for certification of software and firmware in information systems in order to select approaches and tools for working in non-standard situations in a constantly changing regulatory and methodological framework and possible threats to their information security. The type of certification under consideration is limited to methods and techniques for analyzing vulnerabilities and undeclared capabilities. This type of certification is intended for software research. Not all possible aspects related to this type of certification have been considered, however, the novelty and advantages of the approaches are based on some original approaches in cases where it is not clear how to present sets of input data for testing. Approaches to certification tests are presented using tools of our own design, which allows you to identify the main parameters necessary for assembling software and its research, and to parse software written in various programming languages. Based on the program of testing and verification of the object of assessment in accordance with the requirements of information security under a certain level of control, methods for conducting certification studies are proposed, the advantages of approaches using the available and proposed tools are shown. To save on the purchase of tools, some well-known, free and freely distributed tools, as well as effective and inexpensive software products, are proposed for use in tests.

Evaluation of Fast Diffusion Kurtosis Imaging Using New Software Designed for Widespread Clinical Use.

Clinical research using restricted diffusion-weighted imaging, especially diffusion kurtosis (DK) imaging, has been progressing, with reports on its effectiveness in the diagnostic imaging of cerebral infarctions, neurodegenerative diseases, and tumors, among others. However, the application of DK imaging in daily clinical practice has not spread because of the long imaging time required and the use of specific software for image creation. Herein, with the aim of promoting clinical research using DK imaging at any medical facility, we evaluated fast DK imaging using a new software program. We developed a new macro program that produces DK images using general-purpose, inexpensive software (Microsoft Excel and ImageJ), and we evaluated fast DK imaging using bio-phantoms and a healthy volunteer in clinical trials. The DK images created by the new software with diffusion-weighted images captured with short-time imaging sequences were similar to the original DK images captured with long-time imaging sequences. The DK images using three b-values, which can reduce the imaging time by 43%, were equivalent to the DK images using five b-values. The DK imaging technique developed herein might allow any medical facility to increase its daily clinical use of DK imaging and easily conduct clinical research.

Identification of a Panel of Biomarkers for the Early Detection of Ovarian Cancer

According to the CDC, in the United States, Ovarian Cancer is the second most prevalent form of gynecologic cancer and is the fifth leading cause of mortality in women. The only reliable method to screen for this cancer is TVS (trans-vaginal sonography), which is both invasive and costly. The goal of this project was to use the mRMR (Maximum Relevance Minimum Redundancy) Feature Selection Algorithm to select a panel of biomarkers from the Ovarian Cancer dataset and create a non-invasive and inexpensive software tool that could help validate the panel and assist with the early detection of Ovarian Cancer, with a reasonable level of sensitivity.
 This project uses an ovarian cancer dataset with 49 features. The mRMR filter method [9, 10, 12]of feature selection eliminates the redundant features while keeping the relevant features that impact the target class. This project accomplished the final goal of creating a working web application that asks a clinician to provide a few basic blood test results and generates a prediction. The machine learning model [7] used by the application is Random Forest Machine Learning model which is created with the K best features picked by the mRMR algorithm and is successfully utilized to predict the disease and treatment targets thus helping with reducing the mortality rate from ovarian cancer. 
 This project used the Random Forest Classifier model machine learning model. It has been shown to work well with smaller datasets (as with this project’s dataset) and had a sensitivity score of 0.96.

Methodology for designing robotic systems based on CAD Intel Quartus Prime.

At present, programmable logic integrated circuits (FPGAs) are increasingly used in the development of robotic systems. A significant advantage of FPGAs is their versatility and the ability to quickly program to perform the functions of almost any digital device of a robotic system. FPGA is a semi-finished product, on the basis of which a developer with a personal computer has the ability to design a digital device in record time. This is provided by simple and relatively inexpensive software hardware and special software called computer-aided design (CAD). FPGA is an electronic component used to create digital integrated circuits. Unlike conventional digital chips, the logic of FPGA operation is set by programming using special tools: programmers and software. FPGA programming is performed using the description languages Verilog HDL and VHDL. At the upper level, these languages are very similar - the hardware model is described in the form of interacting blocks (modules) and for each of them is defined interface and implementation. Module interfaces describe the input, output, and two-way ports through which modules connect to each other for data exchange as well as control signals. The implementation sets the elements of the internal state and the order of calculating the values of the output interfaces based on this state and the values of the input ports, as well as the rules for updating the internal state. The article reveals the stages of designing digital devices of robotic systems using FPGA, considers the principles of construction and operation of the main nodes of combinational circuits, logical elements implemented one of the specified functions, which is subsequently programmed on FPGA using CAD Quartus Prime with built-in simulators Models.

Optimization of a 660 MWe Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management. Part 2. Power Generation

Modern data analytics techniques and computationally inexpensive software tools are fueling the commercial applications of data-driven decision making and process optimization strategies for complex industrial operations. In this paper, modern and reliable process modeling techniques, i.e., multiple linear regression (MLR), artificial neural network (ANN), and least square support vector machine (LSSVM), are employed and comprehensively compared as reliable and robust process models for the generator power of a 660 MWe supercritical coal combustion power plant. Based on the external validation test conducted by the unseen operation data, LSSVM has outperformed the MLR and ANN models to predict the power plant’s generator power. Later, the LSSVM model is used for the failure mode recovery and a very successful operation control excellence tool. Moreover, by adjusting the thermo-electric operating parameters, the generator power on an average is increased by 1.74%, 1.80%, and 1.0 at 50% generation capacity, 75% generation capacity, and 100% generation capacity of the power plant, respectively. The process modeling based on process data and data-driven process optimization strategy building for improved process control is an actual realization of industry 4.0 in the industrial applications.

SoftBV - a software tool for screening the materials genome of inorganic fast ion conductors.

The identification of materials for advanced energy-storage systems is still mostly based on experimental trial and error. Increasingly, computational tools are sought to accelerate materials discovery by computational predictions. Here are introduced a set of computationally inexpensive software tools that exploit the bond-valence-based empirical force field previously developed by the authors to enable high-throughput computational screening of experimental or simulated crystal-structure models of battery materials predicting a variety of properties of technological relevance, including a structure plausibility check, surface energies, an inventory of equilibrium and interstitial sites, the topology of ion-migration paths in between those sites, the respective migration barriers and the site-specific attempt frequencies. All of these can be predicted from CIF files of structure models at a minute fraction of the computational cost of density functional theory (DFT) simulations, and with the added advantage that all the relevant pathway segments are analysed instead of arbitrarily predetermined paths. The capabilities and limitations of the approach are evaluated for a wide range of ion-conducting solids. An integrated simple kinetic Monte Carlo simulation provides rough (but less reliable) predictions of the absolute conductivity at a given temperature. The automated adaptation of the force field to the composition and charge distribution in the simulated material allows for a high transferability of the force field within a wide range of Lewis acid-Lewis base-type ionic inorganic compounds as necessary for high-throughput screening. While the transferability and precision will not reach the same levels as in DFT simulations, the fact that the computational cost is several orders of magnitude lower allows the application of the approach not only to pre-screen databases of simple structure prototypes but also to structure models of complex disordered or amorphous phases, and provides a path to expand the analysis to charge transfer across interfaces that would be difficult to cover by ab initio methods.

English

Most of the mouse experiments tend to generate a large-scale data, which is needed to be stored and eventually made publicly available. Many research groups still struggle to have central storage and integrated management system of this metadata. Some existing tools like Microsoft excel sheets and couple other colony management web/cloud-based tools are either cumbersome or expensive. There seems a constant need for such inexpensive and uncomplicated colony management software with specific individual database solutions. In addressing this concern, a database application has been developed to meet most of the requirements of such management. RodentSQL is a database application that integrates mouse colony management. It keeps records of phenotype and genotype data for comprehensive data analysis and mining. It is a user-friendly secure system for managing your mouse colony resources. RodentSQL can be used exclusively for mouse colony management for smaller projects or large-scale facilities. Its usage in beta users for managing data of Syrian hamstring mouse has successfully been tested. RodentSQL is offered to the scientific community as open source community software. Key words: Recordkeeping, SQL database, Rodent, transgenic, colony management.

RodentSQL: a software suite for colony management of animal protocols.

Aim:Animal experiments tend to generate large-scale data. Some existing tools like Microsoft Excel and colony management cloud-based tools are either cumbersome or expensive. There is a need for an inexpensive and uncomplicated colony management software with specific individual database solutions.Methods:We have developed a database application named RodentSQL to meet most of the requirements of such animal colony management programs.Results:We present a user-friendly secure system for managing records of phenotype, genotype and metadata for comprehensive data analysis and mining. RodentSQL can be altered based upon user needs. We have successfully tested its usage in beta users for managing data of hamsters and mice.Conclusion:A central facility can share and benefit from this colony management system. RodentSQL can increase workflow efficiency and data security leading to significant cost savings and enhanced scientific results. RodentSQL is offered to the scientific community as an open source software.

Developing a Digital Algorithm for Cognitive Apprenticeship in First-Year Medical School Physiology

Medical school instructors face a challenge in covering high volumes of material with a large group of students, in a short period of time. Unfortunately, this often means that not all concepts will be sufficiently communicated, understood, and recalled. Internet videos (e.g., Khan Academy), have made it easier for educators to curate course content online, and while the prospect of simply shifting course material out of live instructional time towards recorded online formats is tempting, it is a zero-sum game—medical students still will grapple with overwhelming volumes of information and challenging concepts. Instead, we propose that instructors make use of existing student interactions during office hours to efficiently collect information about student mental models and then use and inexpensive presentation-recording software to create short, targeted videos that disseminate recommended alterations to the presented student mental models. We developed this algorithm in a first-year medical physiology course—which can be highly conceptual and require students to go through multiple iterations of conceptual models. 92.5% of students responded “the videos enhanced their learning in physiology. Nine-three percent of students said the videos helped explain a difficult concept. However, analysis of exam scores suggested that the videos did not improve performance. Based on this feedback, we believe that our algorithm does have a positive impact on student learning experiences, and may have an unmeasured effect on student performance. In sharing this work, we hope to encourage other medical educators to document, analyze and evaluate their pedagogical experiences, frame them in theory, and publish them in an academic format. We believe that the majority of medical educators currently teaching students have excellent training in other domains evaluation and analysis and hope to see such talents pointed towards the field of medical education.

ADS-Bsec: A novel framework to secure ADS-B

Abstract The Automatic Dependent Surveillance Broadcast (ADS-B) protocol can be used as a complement to Radar-based Air Traffic Control (ATC), or as a replacement in areas where the latter is impractical. However, ADS-B messages do not include any integrity or authenticity thus they can be easily tampered using inexpensive hardware and open source software. Modifying ADS-B message format is infeasible because it would render the already large implemented base obsolete. This paper proposes ADS-Bsec, which addresses the ADS-B limitations while being compatible with the installed base. ADS-Bsec provides the missing integrity and authenticity into ADS-B packets using a key management infrastructure without altering the existing packet format. This paper also argues for including the proposed framework as a component of the NextGen infrastructure based on our experience in prototyping efforts using cognitive radios, cryptography and multilateration together with existing radar-based ATC systems.

DOCUMENTATION OF OLD TURKIC RUNIC INSCRIPTIONS OF THE ALTAI MOUNTAINS USING PHOTOGRAMMETRIC TECHNOLOGY

Abstract. Old Turkic runic inscriptions of the Altai Mountains (8th–9th centuries AD) were digitized in the course of this project to be preserved in the current state on the Web and deciphered by linguistic experts. The ways the inscriptions were made as well as their location in hardly accessible areas required finding an inexpensive solution that would provide detailed 3D documentation of rock faces, while at the same time mobility and autonomy. Digital photogrammetry came as a quite affordable and optimal choice for getting high-quality outcomes using inexpensive software and further data processing using free software.

Expedited digital appraisal for regular archivists: an MPLP-type approach

Working with a German state archives, the author developed a MPLP approach to digital appraisal/processing. Testing 10 deduplication software (80% failed), she selected a user friendly and inexpensive software. She appraised 670 GB in four days and developed a simple workflow of broad and in-depth qualitative appraisal. The author highlights the importance of appraisal factors, presents a list of desirable software features, and calls for the establishment of peer-reviewed online testing sites administered by archival organizations.

FLAT VERSUS HEMISPHERICAL DOME PORTS IN UNDERWATER PHOTOGRAMMETRY

Abstract. Underwater photogrammetry, like its counterpart in 'air', has gained an increasing diffusion thanks to the availability of easy-to-use, fast and often quite inexpensive software applications. Moreover, underwater equipment that allows the use of digital cameras normally designed to work in air also in water are largely available. However, for assuring accurate and reliable 3D modelling results a profound knowledge of the employed devices as well as physical and geometric principle is even more crucial than in air. This study aims to take a step forward in understanding the effect of underwater ports in front of the photographic lens. In particular, the effect of dome or flat ports on image quality in 3D modelling applications is investigated. Experiments conducted in a semi submerged indust rial structure show that the tested flat port performs worse than the dome, providing higher image residuals and lower precision and accuracy in object space. A significant different quality per colour channel is also observed and its influence on achievable processing results is discussed.

Systematic Pedagogy to Line Balancing with EXCEL

Over the past ten years, simple and inexpensive operations research software that is user friendly to the mentor, student, and instructor has become difficult to obtain. This is especially true since Emmons, Flowers, Khot, and Mathur’s STORM 4.0 for Windows is obsolete for current 32 and 64 bit operating systems and no longer in print. After a diligent product and literature search, it appears there is no adequate inexpensive software that is easily available. Assembly line balancing algorithms are heuristic methods used for balancing operations or production lines. However, most methods employ complex calculations that are challenging to the mentor and mentee. This paper presents a pedagogy from a systems approach using Microsoft EXCEL. The object is to prepare a spreadsheet file with four separate worksheets that are linked to the first worksheet. The step-by-step systematic approach allows the entry on the main worksheet of data such as an annual demand, annual time available, and process times. When the user changes these data entry points, the efficiencies of each operating or production line are automatically re-computed for all three shifts. Worksheets use one of the several available heuristics to compute cycle times (required time between process activities) and transfers it to one, two, or three shifts (worksheets two, three, or four). Once the spreadsheet and accompanying worksheets were completed, the results were compared to several different heuristic algorithms. When authors were satisfied that the results were accurate and not significantly different from other examined algorithms, the final step was to develop a working pedagogy to efficiently describe the process. This allows the user an efficient analytical tool to illustrate and explain interactions within a given process. A local manufacturing facility used this method as a part of a monthly effort to increase line efficiency for individual workstations. The project’s results were satisfactorily tested in a production operations class. The major advantage to the practitioner, engineer, instructor, and student is that EXCEL is readily available on all personal computers, easily understood, and is very practical. Students with very little exposure to line balancing were able to master the method within the first hour of exposure.

Integrated Free Energy Model (IFEM) for microemulsions

The Integrated Free Energy Model (IFEM) is a platform used to predict the solubilization of nonpolar oils in nonionic alkyl-polyethylene oxide (CXEOY) micelles starting from a free energy balance of costs and gains when surfactants from empty micelles and oil from a continuous oil phase assemble to form an oil-swollen micelle. IFEM considers lipophilic interactions between surfactant tails and oil solubilized in the core of micelles, and the interaction between surfactant tails and the oil solubilized in the surfactant tail domain, as well as oil–oil and surfactant–surfactant tail interactions. Expressions to calculate these lipophilic interactions from van der Waals (VDW) interaction potential were introduced in a previous publication. In this article, two new surfactant–water interactions are considered, surfactant headgroup dehydration during solubilization, and surfactant tail group dehydration. These six interaction terms, in addition to two entropy of mixing contributions (in the lipophilic and in the hydrophilic domains) make up the eight terms of the IFEM platform. Of these terms, only the headgroup dehydration requires a calibrated parameter. After calibrating this parameter, the model is capable of predicting experimental solubilization data, and the experimental trends reflected by a semi-empirical model, the Hydrophilic–Lipophilic-Difference+Net-Average-Curvature (HLD–NAC). Although there are numerous approaches to predict the surfactant–oil–water (SOW) phase behavior, the IFEM platform is the only one, to the knowledge of the authors that produces an explicit connection between molecular interactions and experimental data for real SOW systems. The IFEM platform can be programmed in a personal computer using relatively inexpensive software and its explicit nature opens the possibility to introduce additional interaction terms for more complex SOW systems.

Telementoring for airway management between a far forward special operations location to a major medical center using inexpensive telemedicine solutions.

Critically ill patients in remote settings have limited access to specialized care. Telemedicine/telementoring can improve access to quality care, although VTC equipment is costly. This study showed that an inexpensive internet telecom software program can be effectively employed in the intubation training of a remote trainee.

Low-cost single-camera imaging system for aerial applicators

Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. Although various airborne imaging systems are available, most of these systems are either too expensive or too complex to be of practical use for day-to-day aerial application operations. The objective of this study was to develop a low-cost, user-friendly imaging system that can be easily installed on aerial applicators. An imaging system was assembled using off-the-shelf electronics. The system consisted of a digital camera to capture color images, a GPS receiver to geotag images, a video monitor to view live images, and a remote control to trigger the camera. The camera was attached to an aerial applicator and the GPS unit and video monitor were installed in the cockpit. The parameters of the camera were optimized to acquire images under various altitudes, speeds, and ground cover conditions. Geotagged images taken from individual sites or large areas were viewed and mosaicked together using free and inexpensive software. Aerial applicators can assemble such a system and use it to generate additional revenues from remote sensing services. Analysis of sample images has shown that the imaging system has potential for crop condition assessment and pest detection.

Los académicos en las redes sociales: La visibilidad de la investigación académica y la amplificación del público

With Web 2.0 and online social networks, the contemporary idea of networking finds its application also within the academia, thereby allowing free access to scientific work through voluntary sharing of the scholar researchers/authors. This article investigates the tools that facilitate such amplification and its possible outcomes in the short and middle run. The explosion of user-created media content on the web in the past decade unleashed a new media universe, which was made possible by free web platforms and inexpensive software tools which enable people to share their media and easily access media produced by others. Besides the changes in the structure of the web, rapidly fallen costs and increased speed of internet connection also allowed for higher possibilities for collaboration, participation and amplification of audience for academic research.