Use Of Software Research Articles

PO0210: Evaluating the Pre-Clinical Release of a Commercial Auto-Contouring Software for Use in CT-Based Gynecological Brachytherapy

PO0210: Evaluating the Pre-Clinical Release of a Commercial Auto-Contouring Software for Use in CT-Based Gynecological Brachytherapy

Electrophysical cardiac remodeling at the molecular level: Insights into ryanodine receptor activation and calcium-induced calcium release from a stochastic explicit-particle model

We present the first-ever, fully discrete, stochastic model of triggered cardiac calcium dynamics. Using anatomically accurate subcellular cardiac myocyte geometries, we simulate the molecular players involved in calcium handling using high-resolution stochastic and explicit-particle methods at the level of an individual cardiac dyadic junction. Integrating data from multiple experimental sources, the model not only replicates the findings of traditional in silico studies and complements in vitro experimental data but also reveals new insights into the molecular mechanisms driving cardiac dysfunction under stress and disease conditions. We improve upon older, nondiscrete models using the same realistic geometry by incorporating molecular mechanisms for spontaneous, as well as triggered calcium-induced calcium release (CICR). Action potentials are used to activate L-type calcium channels, triggering CICR through ryanodine receptors (RyRs) on the surface of the sarcoplasmic reticulum. These improvements allow for the specific focus on the couplon: the structure-function relationship between L-type calcium channel and RyR. We investigate the electrophysical effects of normal and diseased action potentials on CICR and interrogate the effects of dyadic junction deformation through detubulation and orphaning of RyR. Our work demonstrates the importance of the electrophysical integrity of the calcium release unit on CICR fidelity, giving insights into the molecular basis of heart disease. Finally, we provide a unique, detailed, molecular view of the CICR process using advanced rendering techniques. This easy-to-use model comes complete with tutorials and all necessary software for use and analysis so as to maximize usability and reproducibility. Our work focuses on quantifying, qualifying, and visualizing the behavior of the molecular species that underlie the function and dysfunction of subcellular cardiomyocyte systems.

Optimizing the Effectiveness of Moving Target Defense in a Probabilistic Attack Graph: A Deep Reinforcement Learning Approach

Moving target defense (MTD) technology baffles potential attacks by dynamically changing the software in use and/or its configuration while maintaining the application’s running states. But it incurs a deployment cost and various performance overheads, degrading performance. An attack graph is capable of evaluating the balance between the effectiveness and cost of an MTD deployment. In this study, we consider a network scenario in which each node in the attack graph can deploy MTD technology. We aim to achieve MTD deployment effectiveness optimization (MTD-DO) in terms of minimizing the network security loss under a limited budget. The existing related works either considered only a single node for deploying an MTD or they ignored the deployment cost. We first establish a non-linear MTD-DO formulation. Then, two deep reinforcement learning-based algorithms are developed, namely, deep Q-learning (DQN) and proximal policy optimization (PPO). Moreover, two metrics are defined in order to effectively evaluate MTD-DO algorithms with varying network scales and budgets. The experimental results indicate that both PPO- and DQN-based algorithms perform better than Q-learning-based and random algorithms. The DQN-based algorithm converges more quickly and performs, in terms of reward, marginally better than the PPO-based algorithm.

Determination of refractive index of liquids using a machine vision sensor and a programmable device

Abstract In this implementation, it is proposed a measurement method and/or educational-demonstrative resource that determines the refractive index of a liquid. A method can be found in the literature which relates the diameter of an object to the diameter of its amplified image when it is introduced in a container filled with the liquid on an unknown refractive index. Therefore, this proposal is based on measuring the diameter of the amplified image related to a cylindrical object immersed in a beaker, by means of using the color recognition function of an artificial intelligence camera; while the data processing will be carried out with the use of a micro:bit board. Finally, the result will be displayed in a 128 × 64 OLED screen. According to the characteristics and materials used in the proposal, it can be perfectly applied in undergraduate and graduate levels in the field of Physics or Engineering. Furthermore, the proposed device does not require an external computer or specialized software for use, thus also offering easy assembly, portability and automation.

A thermoplastic clay constitutive model with temperature dependent evolution of stress anisotropy

This paper presents a thermomechanical constitutive model that captures temperature dependent evolutions of preconsolidation stress and stress anisotropy in normally consolidated and lightly overconsolidated saturated clays. Following a non-associative flow rule, the model was formulated to account for the rate of evolution of stress anisotropy as a function of temperature. A temperature-dependent rotational hardening parameter was introduced and calibrated employing a simple optimization algorithm for four different clays. The developed model was further implemented in a finite element (FE) analysis software for use in boundary value problems. Success of such numerical implementation and predictive performance of the constitutive model was further verified through FE simulations of drained and undrained triaxial tests on saturated clays at reference and elevated temperature. FEA results obtained from these simulations agreed very well with test data reported in the literature.

ML-Based Software Defect Prediction in Embedded Software for Telecommunication Systems (Focusing on the Case of SAMSUNG ELECTRONICS)

Software stands out as one of the most rapidly evolving technologies in the present era, characterized by its swift expansion in both scale and complexity, which leads to challenges in quality assurance. Software defect prediction (SDP) has emerged as a methodology crafted to anticipate undiscovered defects, leveraging known defect data from existing codes. This methodology serves to facilitate software quality management, thereby ensuring overall product quality. The methodologies of machine learning (ML) and one of its branches, deep learning (DL), exhibit superior accuracy and adaptability compared to traditional statistical approaches, catalyzing active research in this domain. However, it makes it hard to generalize, not only because of the disparity between open-source projects and commercial projects but also due to the differences in each industrial sector. Consequently, further research utilizing datasets sourced from diverse real-world sectors has become imperative to bolster the applicability of these findings. For this study, we utilized embedded software for use with the telecommunication systems of Samsung Electronics, supplemented by the introduction of nine novel features to train the model, and a subsequent analysis of the results ensued. The experimental outcomes revealed that the F-measurement metric has been enhanced from 0.58 to 0.63 upon integration of the new features, thereby signifying a performance augmentation of 8.62%. This case study is anticipated to contribute to bolstering the application of SDP methodologies within analogous industrial sectors.

Target Product Profile for a Machine Learning-Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study.

Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation. This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England. This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence's Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from "definitely exclude" to "definitely include," and suggest edits. The document will be iterated between rounds based on participants' feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote. Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024. The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas. DERR1-10.2196/50568.

МОДЕЛЬ ИДЕНТИФИКАЦИИ АГРЕССИВНЫХ ПРОГРАММНЫХ ЭЛЕМЕНТОВ

The article examines issues of modeling computation processes that help assess the probable capabilities of the software used to negatively affect the operation of various types of human-machine systems, including those with artifi cial intelligence. Given its aggresive behavior, a numerical experiment analyzed software that provides intelligent support to assistant robots for teaching staff and implements certain functions in the smart home’s computation complex. The experiment’s fi ndings raise a number of issues, which are discussed. The study demonstrates an approach for highlighting a set of machine programming language statements capable of producing general and special software bugs that affect the information environment and appropriate operation of smart home components. Guidelines for grouping a set of aggressive properties are given based on the specifi cs of the software in use.

Crise climática: caminhos para enfrentar seus efeitos nas habitações em Curitiba

Abstract The objective of this article is to present paths that can contribute to mitigating the effects of climate change on houses built in the metropolis of Curitiba. The analysis of the occurrence of natural disasters in the state of Paraná demonstrates that the most frequent extreme climatic event is the windstorm, and the Curitiba region is the one that most presented occurrences of windstorms in the analyzed period. Federal laws and municipal plans related to the theme are presented, as well as points that can be adopted as tools to mitigate the impacts of the climate crisis on the city. Finally, it is concluded that, through the concept of demand--side innovation policies with the use of software programs, which simulate the future scenario of climate transformations, it is possible to contribute to the development of resilient housing.

An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units

Particle Image Velocimetry (PIV) is a widely used experimental technique for measuring flow. In recent years, open-source PIV software has become more popular as it offers researchers and practitioners enhanced computational capabilities. Software development for graphical processing unit (GPU) architectures requires careful algorithm design and data structure selection for optimal performance. PIV software, optimized for central processing units (CPUs), offer an alternative to specialized GPU software. In the present work, an improved algorithm for the OpenPIV–Python software (Version 0.25.1, OpenPIV, Tel Aviv-Yafo, Israel) is presented and implemented under a traditional CPU framework. The Python language was selected due to its versatility and widespread adoption. The algorithm was also tested on a supercomputing cluster, a workstation, and Google Colaboratory during the development phase. Using a known velocity field, the algorithm precisely captured the time-average flow, momentary velocity fields, and vortices.

Generation, validation, and benchmarking of a commercial independent Monte Carlo calculation beam model for multi-target SRS

BackgroundDosimetric validation of single isocenter multi-target radiosurgery plans is difficult due to conditions of electronic disequilibrium and the simultaneous irradiation of multiple off-axis lesions dispersed throughout the volume. Here we report the benchmarking of a customizable Monte Carlo secondary dose calculation algorithm specific for multi-target radiosurgery which future users may use to guide their commissioning and clinical implementation. PurposeTo report the generation, validation, and clinical benchmarking of a volumetric Monte Carlo (MC) dose calculation beam model for single isocenter radiosurgery of intracranial multi-focal disease. MethodsThe beam model was prepared within SciMoCa (ScientificRT, Munich Germany), a commercial independent dose calculation software, with the aim of broad availability via the commercial software for use with single isocenter radiosurgery. The process included (1) definition & acquisition of measurement data required for beam modeling, (2) tuning model parameters to match measurements, (3) validation of the beam model via independent measurements and end-to-end testing, and finally, (4) clinical benchmarking and validation of beam model utility in a patient specific QA setting. We utilized a 6X Flattening-Filter-Free photon beam from a TrueBeam STX linear accelerator (Siemens Healthineers, Munich Germany). ResultsIn addition to the measured data required for standard IMRT/VMAT (depth dose, central axis profiles & output factors, leaf gap), beam modeling and validation for single-isocenter SRS required central axis and off axis (5 cm & 9 cm) small field output factors and comparison between measurement and simulation of backscatter with aperture for jaw much greater than MLCs. Validation end-to-end measurements included SRS MapCHECK in StereoPHAN geometry (2%/1 mm Gamma = 99.2% ± 2.2%), and OSL & scintillator measurements in anthropomorphic STEEV phantom (6 targets, volume = 0.1–4.1cc, distance from isocenter = 1.2–7.9 cm) for which mean difference was −1.9% ± 2.2%. For 10 patient cases, MC for individual PTVs was −0.8% ± 1.5%, −1.3% ± 1.7%, and −0.5% ± 1.8% for mean dose, D95%, and D1%, respectively. This corresponded to custom passing rates action limits per AAPM TG-218 guidelines of ±5.2%, ±6.4%, and ±6.3%, respectively. ConclusionsThe beam modeling, validation, and clinical action criteria outlined here serves as a benchmark for future users of the customized beam model within SciMoCa for single isocenter radiosurgery of multi-focal disease.

Exploring the Impact of GeoGebra on Mathematical Proficiency and Inductive Reasoning Ability in Geometry Students of MSU N – Integrated Developmental School

The study aimed to compare the effectiveness of two teaching strategies, one utilizing GeoGebra and the other employing traditional manual drawing tools in the guided discovery activities. A two-group experimental design with a pretest and posttest was used, along with a perception survey as qualitative support. The study was conducted over one grading period, involving a population of 120 Grade 9 students from Mindanao State University at Naawan-Integrated Developmental School. Data were collected through questionnaires and inductive reasoning activity worksheets developed by the teacher, which underwent rigorous reliability and validity testing. The Wilcoxon two-sample paired test results revealed a significant increase in scores from the pretest to the posttest for both the GeoGebra and the Conventional groups. However, the Mann-Whitney U-test and the independent t-Test indicated no significant difference between the two groups' performances in Mathematics proficiency and inductive reasoning activities, respectively. Furthermore, results of the perception survey showed highly positive perceptions of students on using GeoGebra, perceiving it to have enhanced their inductive reasoning ability. Overall, these findings suggest that using GeoGebra is equally effective as using manual drawing implements, having found no significant difference in performance between the two groups. Given these results and the positive review of students on the use of GeoGebra, it is recommended that the software's use be integrated into mathematics instruction.

A Comparative Study of Different Software Complexity Metrics in Measuring Software Interoperability

Software interoperability is crucial for organizations that rely on multiple software systems to perform their operations. However, due to the complexity and variety of software systems, ensuring interoperability can be difficult. Measuring software complexity metrics can be used to identify potential problems and assess how well different interoperability strategies work. In this study, we investigated and compared the effectiveness of different software complexity metrics in measuring software interoperability. We used statistical methods to analyze data collected from a sample of software systems. The results of our study show that certain metrics, such as coupling and cohesion, are more effective than others in measuring software interoperability. By selecting appropriate metrics, developers can ensure better productivity, lower costs, and more adaptable use of software systems. The findings of this study have implications for the creation of software and can guide businesses in choosing the right criteria to achieve software interoperability.

Evaluation of requirement engineering best practices for secure software development in GSD: An ISM analysis

AbstractTechnological advancement makes the world a global village. Security is an evergreen and everlasting area, because of the continuous threat from Hackers and Crackers. The immense use of software systems has modernized human society in every aspect. Thus, it is crucial to devise new processes, techniques, and tools to support teams in the development of secure code from the early stages of the software development process, while potentially reducing the costs and shortening the time to market. Considering the significance of software security, it is important to consider the security practices from the early phase of the software development life cycle (SDLC), that is, requirements engineering (RE). Hence, this study aims to identify and categorize RE practices important to apply for secure software development (SSD) in a geographically distributed development environment. To study the RE practices concerning SSD, we conducted a questionnaire survey with industrial experts in the global software development (GSD) context.Furthermore, the interpretive structure modeling (ISM) approach was applied to evaluate the relationship between the RE security practice core categories. This paper identifies 70 practices and classifies them into 11 fundamental dimensions (categories) to assist GSD organizations in specifying the requirements for SSD. The ISM results show that the “Awareness of Secure Requirement Engineering (SRE)” category has the most decisive influence on the other 10 core categories of the identified RE security practices. With the help of empirical evidence and the ISM approach, this work attempts to identify potential security practices and to give a set of secure RE practices that can be used to improve the security of the software development process.

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review.

Pharmacokinetic nomograms, equations, and software are considered the main tools available for Therapeutic Drug Monitoring (TDM). Model-informed precision dosing (MIPD) is an advanced discipline of TDM that allows dose individualization, and requires a software for knowledge integration and statistical calculations. Due to its precision and extensive applicability, the use of these software is widespread in clinical practice. However, the currently available evidence on these tools remains scarce. To review and summarize the available evidence on MIPD software tools to facilitate its identification, evaluation, and selection by users. An electronic literature search was conducted in MEDLINE, EMBASE, OpenAIRE, and BASE before July 2022. The PRISMA-ScR was applied. The main inclusion criteria were studies focused on developing software for use in clinical practice, research, or modelling. Twenty-eight software were classified as MIPD software. Ten are currently unavailable. The remaining 18 software were described in depth. It is noteworthy that all MIPD software used Bayesian statistical methods to estimate drug exposure and all provided a population model by default, except NONMEN. Pharmacokinetic software have become relevant tools for TDM. MIPD software have been compared, facilitating its selection for use in clinical practice. However, it would be interesting to standardize the quality and validate the software tools.

Comparing Flow-R, Rockyfor3D and RAMMS to Rockfalls from the Mel de la Niva Mountain: A Benchmarking Exercise

Rockfall simulations are often performed at various levels of detail depending on the required safety margins of rockfall-hazard-related assessments. As a pseudo benchmark, the simulation results from different models can be put side-by-side and compared with reconstructed rockfall trajectories, and mapped deposited block fragments from real events. This allows for assessing the objectivity, predictability, and sensitivity of the models. For this exercise, mapped data of past events from the Mel de la Niva site are used in this paper for a qualitative comparison with simulation results obtained from early calibration stages of the Flow-R 2.0.9, Rockyfor3D 5.2.15 and RAMMS::ROCKFALL 1.6.70 software. The large block fragments, reaching hundreds of megajoules during their fall, greatly exceed the rockfall energies of the empirical databases used for the development of most rockfall models. The comparison for this challenging site shows that the models could be improved and that combining the use of software programs with different behaviors could be a workaround in the interim. The findings also highlight the inconvenient importance of calibrating the simulations on a per-site basis from onsite observations. To complement this process, a back calculation tool is briefly described and provided. This work also emphasizes the need to better understand rockfall dynamics to help improve rebound models.

Software for computer simulation of multiphysics processes in electromagnets and actuators of vacuum switching devices taking into account contact interaction of structural elements. Part 2: features of commercial software and open access codes

The first part of the work presented a general overview and classification of software tools for the numerical solution of multiphysics problems of computer modelling of coupled electromagnetic, thermal and mechanical processes in modern complex technical objects, including actuators and electromagnets of vacuum switching devices taking into account contact phenomena when their stress-strain state changes. Criteria for choosing the appropriate software were also proposed and the features of in-house codes for mathematical modelling of technical objects and processes under consideration were analyzed. This paper is the second part of the work and is devoted to a detailed review of commercial codes present on the market and available, as well as open access tools for possible use in performing relevant computational studies, namely, numerical analysis of multiphysics processes in electromagnets and actuators of vacuum switching devices, taking into account contact phenomena by the Finite Element Method. On this basis, taking into account the conclusions regarding in-house codes made in the first part of the work, a selection of specific software for use in the performance of relevant calculation studies is made.

87 An Augmented Reality Burn Management Application to Guide Care in Austere Environments

Abstract Introduction Novel medical technologies are necessary to support virtual health in low bandwidth environments. When tele-mentoring is not possible, advanced clinical decision support tools can deliver essential medical knowledge to assist novice clinicians. These tools can fill knowledge gaps in specialty fields, like burn. We developed the Augmented Reality Burn Assist Manager (ARBAM), a novel, comprehensive augmented reality (AR)-based burn management platform to address key tasks in burn care. Methods A randomized 2x2 cross-over design was used to investigate if ARBAM could enhance a user’s ability to care for a simulated burn patient as compared to standard clinical practice guidelines (CPGs). We developed the software for use on a mixed reality, head-mounted device. Participants were clinicians with little to no burn care experience, and were asked to complete 4 key tasks, twice each, using either paper copies of the Joint Trauma System’s CPGs and supplemental worksheets first (Paper) or our AR technology. Tasks included calculating burn size (TBSA), performing medication dosage calculations (MC), managing a burn fluid resuscitation (FR), and performing a simulated escharotomy (EC). All tasks were evaluated for completion time and accuracy. Cross-over analysis of treatment effects used a two-sided, two-sample t-test or Wilcoxon Rank-Sum test as appropriate. Results Eleven participants were randomized: 5 started with Paper and 6 started with AR. Time to perform FR was statistically different (p< 0.05) with AR taking less time than Paper (4.8 vs. 7.0 mins, respectively). FR clinical performance was also better in the AR group with a mean accuracy score of 99% vs. 52% for Paper (p< 0.001). EC completion times were not clinically or statistically different. However, EC accuracy was 93% for AR compared to 55% for Paper (p< 0.001). Although not statistically different, MC performance accuracy was considerably better for AR (91%) than for Paper (66%). No differences between groups were observed for TBSA or MC completion times nor TBSA accuracy. Conclusions Compared to traditional tools, AR may enhance a clinician's ability to complete key tasks in the initial management of a burn patient. This technology may be helpful during disasters when tele-mentoring is not available. Limitations of this study include a small sample size, limited user training on the AR device, and potential carry-over effects. Therefore, generalizations cannot be made about wide-scale usage. Nonetheless, this study showed that AR may be helpful in managing lifesaving burn tasks. Applicability of Research to Practice ARBAM may enhance decision making by novice clinicians when caring for burn patients. Our data demonstrate the potential for AR-based support tools to improve burn care delivery and reduce error rates for novice clinicians, which could lead to reductions in morbidity and mortality. Future research is needed to investigate how AR technology can be used for other lifesaving interventions.

Image-Guided Programming Tool for DBS Programming Used with a Multiple-Source, Constant-Current System Reduces Initial Programming Time (P4-11.012)

Image-Guided Programming Tool for DBS Programming Used with a Multiple-Source, Constant-Current System Reduces Initial Programming Time (P4-11.012)

MODELING OF PROCESSES OF INDUSTRIAL PREPARATION, PROCESSING AND LIQUEFACTION OF NATURAL GAS

The article presents the results of the development of the modernization of the complex gas preparation installation, namely the modeling of the processes of removing heavy hydrocarbons at the stage of preparing natural gas for transportation. Heavy hydrocarbons, which are removed at this stage, become a separate commodity product in the process of processing. With the use of software systems for computer simulation of technological processes of GazCondNafta and HYSYS, a variant of the modernization of the existing installation of complex gas preparation of the gas condensate field was developed. Options for modeling technological schemes for obtaining target fractions of methane, ethane, propane, butane from natural gas, gas synthesis and pyrolysis gas are given. Bibl. 9, Fig. 5, Tab. 8.