Software Model Research Articles

Tracking the terminal velocity and energy of a parachutist: A video analysis for Physics classroom experiment

Abstract This study primarily focuses on tracking a parachutist’s terminal velocity and energy during a free fall using video analysis. Also, this study looks into related literature about the implications of this experiment for classroom practice. High-quality and slow-motion videos of free-falling slotted masses acting as parachutists were captured, and the terminal velocities and energies were analyzed through software tracker video analysis and modeling. The data from the software revealed that, indeed, the terminal velocity is directly proportional to the square root of the masses. The 200g parachutist reaches terminal velocity first, then the less massive parachutist. The generated kinetic energy, gravitational potential energy, and total mechanical energy graphs were similar to the literature. The tracker video analysis can indeed track a parachutist’s terminal velocity and energy. However, the acceleration due to gravitational needed to be measured correctly due to some errors in the experiment. Furthermore, the literature has cited positive and negative implications for classroom practice. This study can say that the positive outweighs the negative. The positive repercussions were about enhanced engagement, accuracy, and data precision, while the negative ones were about the school’s technological divide.

CROSS Safety Report: Unconservative design of flat slab due to software modelling issues

This month's report discusses how a design/modelling problem caused an under-designed reinforced concrete slab to be constructed.

МЕТОД ОБУЧЕНИЯ ИНТЕЛЛЕКТУАЛЬНОГО АГЕНТА С ПОМОЩЬЮ СЕТЕЙ DOUBLE DQN, ПУТЕВЫХ ТОЧЕК И ФУНКЦИИ ВОЗНАГРАЖДЕНИЯ

The problems of increasing the control efficiency of autonomous vehicles are considered. The problem of reducing the required computational resources for the intelligent vehicle control module is highlighted. A neural network training algorithm for Double DQN architecture with modified reward functions is proposed. The basis of the proposed solution is the use of lane segmentation, reward function and the use of additional waypoints in training. A software model has been developed and simulation of the learning process has been performed. The results obtained from a comparative analysis with known solutions show a stable increase in episode duration, and effective training in a realistic urban simulation. The study points to the possibility of reducing the need for high computing power, which will enable the use of central processing units (CPUs) for basic functions of unmanned vehicles instead of graphics processing units (GPUs).

The Analysis Factors Influencing the Implementation of Digital Social Entrepreneurship Application in Learning Engineering Education Using Structural Equation Modelling

A big part of being an entrepreneur is keeping up with modern technological advancements. However, many factors can lead to the ambition to launch an online company. Digital social entrepreneurship methodology examines the effects of college students' entrepreneurial mindset, smartphone usage habits, and Locus of Control on their digital business intentions. This research is fundamental because it provides information to universities that they can use to evaluate their plans for a digital-based entrepreneurship learning model that will help them provide a good education. This study involved 428 respondents, and the data obtained from the respondents were examined using the application of structural equation modeling with a survey approach for this research, which looks at a small portion of the community and collects data through questionnaires. The primary data was examined using SmartPLS 4.0 software and structural equation modeling. This study found that having an entrepreneurial mindset, smartphone use, and locus of control exerts a substantial and meaningful impact on one's aspiration to become a digital entrepreneur. We wanted to find out how college students' thinking about being an entrepreneur affects their desire to become a digital entrepreneur, using smartphone usage habits and locus of control as influencing factors. To make someone who wants to become an entrepreneur, this research needs to measure Digital Entrepreneurial Intention appropriately in students who take Entrepreneurship courses.

An Analysis Management by Mike 21 Modelling at Rolak 70 Retention Pool in Jombang Regency, East Java Province, Indonesia

Some areas in Indonesia have high level of sedimentation problems that able to cause flooding, and one apparent solution is to build a retention pool. Sedimentation is deposition of material into the reservoir or dam due to environmental damage or erosion occurs in the river basin area. Sedimentation becomes the main factor in constructing the Rolak 70 Retention Pool, as an important component in controlling floods on the Konto River when the water discharge exceeds the maximum limit. From geography perspective, the modelling location is in waters located between 112° 11′ 22.85″ South Latitude and 7° 38′ 42.23″ East Longitude. The model area has northern boundary at the tip of Rolak 70 pool, while western boundary at the outlet of Rolak 70 pool. The lowest water depth value is located in upstream area of Konto River at coordinates of 112°11’27.81″ South Latitude and 7°38’49.27″ East longitude. Weight of soil sample taken from the research site was ± 1000 grams at each point, and the result of sediment sample test performed at the Soil Mechanics Laboratory of Civil Engineering Department, Sultan Agung University, Semarang showed that the research area is dominated by sand, followed by mud and gravel. There were several tests conducted include grain size analysis, hydrometer analysis, and specific gravity analysis to determine the D50 of the sediment. In the study area, several sampling points were taken, started from upstream area of the river in front of Rolak 70 building to the Rolak 70 Retention Pool. For this purpose, a MIKE 21 software modelling was used to determine distribution and lines of sedimentation in the study area. As visible from changes found in bed level morphology that occurred in Rolak 70 Retention Pool by cross section extraction, it can be seen that the largest change occurred in analysis for line 1 and the smallest bed level changes occurred in the analysis for line 6. Then, the result revealed that sedimentation tends to occur at large locations in upstream area of Rolak 70 Retention Pool, while the smallest sedimentation potential will happen at the downstream area of Rolak 70 Retention Pool. These results can be caused by changes of speed from the river flow which tends to decrease towards the end of Rolak 70 Retention Pool. So, the river flow has no more energy to carry heavy amount of sediments originating from the upstream area of the Konto River. By the existence of this retention pool, the need for rice field irrigation will not be disturbed by sediment deposits. In addition, the Rolak 70 Retention Pool can be used as temporary storage for material from Mount Kelud eruption where these materials can be utilized as building material or other useful purposes.

Recent trends in oil and gas geology software modeling

Recent trends in oil and gas geology software modeling

Indang Konektayo Kiosk: An Interactive Menu System for Tourists

Every traveler wants to experience hassle-free and safe travel while maintaining an enjoyable journey with the help of user-friendly interfaces and an innovative technological menu system. An interactive information menu system that improves the traveler experience, commercial operations, and tourism information at the Municipality of Indang. It is a technological solution that is relevant to today's demand and interest, and that is readily available data sources and information, which benefit. Specifically, it possesses the following characteristics, including: (1) a place finder that provides registered places in Indang with the right information and allows users to discover new established places in Indang; (2) mapping routes that provide directions and generate routes; and (3) sending the Google Maps URL through a short messaging system (SMS) to the mobile phone of the user, which can be opened in digital maps such as Google Maps. The descriptive method of research was used in this study and was created with Cascading Style Sheet (CSS), Hypertext Markup Language (HTML), Hypertext Processor (PHP), JavaScript (JS) in web development, MySQL for its database, as well as an SMS API for sending map URLs based on the queries. The Agile software model was used, which was composed of sprints, each of which was meant to focus on the developmental adjustments as interactive kiosks were prone to updates and ran into serious changes. Using ISO 9126 software product quality standards, the system received an average rating of 4.71 from respondents, indicating excellent quality and that it served its functions properly and met all of the required requirements.

Reliability inference of a multicomponent stress-strength model for exponentiated Pareto distribution based on progressive first failure censored samples

Multicomponent stress-strength (MC-SS) analysis is crucial for risk management and decision-making in various fields such as engineering, manufacturing, and quality control. It helps in identifying vulnerable components and areas where improvements can enhance overall system reliability. A primary contribution of this research is the implementation of the progressive first-Failure censored (PFIF-C) scheme. This scheme offers a novel and efficient approach to time and cost censoring, surpassing many existing censoring schemes found in the literature. The current study investigates the issue of MC-SS reliability inference under PFIF-C from the exponentiated Pareto distribution. The reliability of the MC-SS system is considered under the condition that both stress and strength follow an exponentiated Pareto distribution with a common second shape parameter. The parameter estimates and reliability estimate of the MC-SS system is produced using the maximum likelihood and Bayesian procedures. The asymptotic confidence intervals and highest posterior density credible intervals for the MC-SS system reliability are produced. Bayesian estimates are yielded using Markov Chain Monte Carlo under both informative and non-informative priors, considering symmetric and asymmetric loss functions. In order to assess the efficacy of the suggested methodology, simulation analyses are conducted. According to the simulation data Bayesian estimates of the MC-SS reliability, employing both symmetric and asymmetric loss functions, consistently outperform maximum likelihood estimates in terms of estimated risks. In general, Bayesian estimates based on asymmetric loss function perform better than the other competing loss function. The procedure is further shown with one real-world data example about failure times of a specific software model to show how the recommended approach may be applied to assess the strength and stress of a multicomponent model.

Assessing the Effect of Head and Neck Orientation on Head Injury Parameters in Taekwondo

Background: Brain injuries may be caused by the linear and rotational acceleration of the head and neck; in fact, head and neck orientation are one of the factors determining the type and severity of brain injury when the impact delivered to head is a less important consideration. This investigation has analyzed the effect of head and neck orientation on linear and rotational acceleration in Taekwondo. Methods: The ADAMS software model has been used to determine the linear and rotational acceleration in the taekwondo roundhouse kick in various orientations. Results: The results revealed that the maximum linear and rotational acceleration was related to neck 0° were 99g, and 4576 , respectively. The head and neck orientation did not affect the magnitude of the linear and rotational acceleration in the sagittal plane. However, as the angle of the head and neck orientation increased in the frontal plane, the magnitude of the linear and rotational acceleration decreased. Conclusion: In general, the results indicate that only rotational acceleration was the cause of brain injury in taekwondo. Increasing the angle of orientation of the head and neck in frontal plane would lead to a reduction in intensity.

A software reliability growth model for open-source software using sine cosine algorithm

A software reliability growth model for open-source software using sine cosine algorithm

Laboratory Tests in Cyber-Physical Mode for an Energy Management System Including Renewable Sources and Industrial Symbiosis

Abstract The aim of this paper regards the laboratory validation of an energy management system (EMS) for an industrial site on the Eigerøy island (Norway). It will be the demonstration district in the ROBINSON project for a consequent concept replication. This activity in cyber-physical mode is an innovative approach to finalize the EMS tool with real measurement data with prime movers available at laboratory level, considering the necessary EMS robustness and flexibility for replication on other industrial islands. This EMS was designed and developed to minimize variable costs, producing on/off and set-point signals that, through a model predictive control (MPC) software, establish the system status. This smart grid includes renewable sources (e.g., solar panels, a wind turbine, and syngas) and traditional prime movers, such as a steam boiler for the industry needs. Moreover, an energy storage device is installed composed of an electrolyzer with a hydrogen pressure vessel. The main results reported in this work regard 26-h tests performed in cyber-physical mode thanks to the real-time interaction of hardware and software. So, a real microturbine and real photovoltaic (PV) panels were managed by the EMS in conjunction with software models for components not physically present in the laboratory. Although the optimization target was cost minimization, significant improvement was also obtained in terms of efficiency increase and CO2 emission decrease.

Circular-ring tied arc loaded excellent metamaterial absorber for EMI shielding of Wi-Fi signal and impurity sensing of cooking oil

This paper demonstrates a unique symmetric structure excellent metamaterial absorber (MMA) loaded with circular-ring tied arcs. The FR4 substrate-based MMA can accomplish 98.88 % and 99.81 % absorption maximums at the Wi-Fi and 5G frequencies of 2.4 GHz and 5.0 GHz respectively. The unit cell dimension of 0.16λ0×0.16λ0×0.0128λ0 is considered where the wavelength, λ0 is calculated at 2.4 GHz. The performance of the absorber is analyzed through the electric field, magnetic field, surface current, and effective parameters. The dimensions are optimized through the parametric analysis of the developed model in CST software. The model exhibits stability up to 60° for Transverse electric and magnetic polarizations. During electromagnetic interference (EMI) shielding demonstration, it can achieve a high shielding effectiveness (SE) of 54.34 dB at 2.4 GHz and 77.96 dB at 5.0 GHz. For sensing operation, it can attain a quality factor (Q-factor) of 25.61, a sensitivity of 3.30 %, and a figure of merit (FoM) of 84.51. The prototype measurements of the MMA for EMI shielding and impurity sensing of oil samples have a strong correlation with the simulation performance. Because of the high SE, Q-factor, sensitivity, and FoM, the developed MMA can be a competitive candidate in EMI shielding and oil impurity sensing applications.

Model for detecting metastatic deposits in lymph nodes of colorectal carcinoma on digital/ non-WSI images

IntroductionColorectal cancer (CRC) constitutes around 10% of global cancer diagnoses and death due to cancer. Treatment involves the surgical resection of the tumor and regional lymph nodes. Assessment of multiple lymph node demands meticulous examination by skilled pathologists, which can be arduous, prompting consideration for an artificial intelligence (AI)-supported workflow due to the growing number of slides to be examined, demanding heightened precision and the global shortage of pathologists.MethodThis was a retrospective cross-sectional study including digital images of glass slides containing sections of positive and negative lymph nodes obtained from radical resection of primary CRC. Lymph nodes from 165 previously diagnosed cases were selected from Agha Khan University Hospital, from Jan 2021 to Jan 2022. The images were prepared at 10X and uploaded into an open source software, Q path and deep learning model Ensemble was applied for the identification of tumor deposits in lymph node.ResultsOut of the 87 positive lymph nodes detected by AI, 73(84%) were true positive and 14(16%) were false positive. The total number of negative lymph nodes detected by AI was 78. Out of these, 69(88.5%) were true negative and 9 (11.5%) were false negative. The sensitivity was 89% and specificity 83.1%. The odds ratio was 40 with a confidence interval of 16.26–98.3. P-value was < 0.05 (< 0.0001).ConclusionThough it was a small study but its results were really appreciating and we encourage more such studies with big sample data in future.

Advanced Prediction of Hepatic Oncogenic Transformation in HBV Patients via RNA-Seq Data Analysis and Deep Learning Techniques.

Liver cancer, recognized as a significant global health issue, is increasingly correlated with Hepatitis B virus (HBV) infection, as evidenced by numerous scientific studies. This study aims to examine the correlation between HBV infection and the development of liver cancer, focusing on using RNA sequencing (RNA-seq) to detect HBV sequences and applying deep learning techniques to estimate the likelihood of oncogenic transformation in individuals with HBV. Our study utilized RNA-seq data and employed Pathseq software and sophisticated deep learning models, including a convolutional neural network (CNN), to analyze the prevalence of HBV sequences in the samples of patients with liver cancer. Our research successfully identified the prevalence of HBV sequences and demonstrated that the CNN model achieved an exceptional Area Under the Curve (AUC) of 0.998 in predicting cancerous transformations. We observed no viral synergism that enhanced the pathogenicity of HBV. A detailed analysis of sequences misclassified by the CNN model revealed that longer sequences were more conducive to accurate recognition. The findings from this study provide critical insights into the management and prognosis of patients infected with HBV, highlighting the potential of advanced analytical techniques in understanding the complex interactions between viral infections and cancer development.

An innovative approach to automate BIM data retrieval and processing for building acoustic comfort calculations based on the IFC standard

Nowadays, there is a growing demand for deep renovation projects aimed at improving the energy efficiency of buildings while enhancing indoor comfort conditions for the inhabitants, both thermal and acoustic. To design effective renovation strategies, technicians need to know the current state of the building to propose acoustic or only thermal improvements. However, evaluating indoor acoustic comfort requires time-consuming and tedious calculations, which can be prone to errors when handled manually. While Building Information Modelling (BIM) can facilitate this process by leveraging the extensive contained data and offering the potential to automate these processes, such automation is not yet widespread. Typically, only geometric data is retrieved automatically from BIM models in acoustic software, while acoustic parameters must be provided manually. This paper addresses these challenges by introducing a novel approach that integrates automated data extraction from BIM with acoustic simulation tools. Specifically, an Extract, Transform and Load (ETL) solution was designed to automatically retrieve both geometric and acoustic data for an Acoustic Comfort tool, which calculates an estimation of indoor acoustic comfort, from an Industry Foundation Classes (IFC). This approach was tested in a demonstration case located in Spain, showing a significant reduction in processing time and increased accuracy compared to traditional methods of manually extracting data from BIM for acoustic assessment. This research represents a significant advance in acoustic simulations by integrating IFC data with automated processing, improving accuracy and offering practical advantages for developing more efficient and reliable BIM-based applications, thus supporting the design of deep renovation projects.

GIS-technologies and algorithm for developing regional systems for handling medical waste on the example of three regions

Introduction. GIS is a modern computer technology designed for collecting, storing, analyzing and visualizing spatial data – mapping. GIS is also actively used in healthcare to solve many regional problems, including optimization and management of healthcare resources. Over last decade, many researchers have used mathematical software models for healthcare waste management. A review of the literature shows facility location, risk to the public, and economic feasibility to be among the issues that have been extensively covered in the literature. Designing a reverse logistics network using mathematical software tools is an efficient and effective way to manage healthcare waste. The objective of the study. To determine the optimal approach to creating a functional model of a system for managing medical waste of class B and C using GIS-technologies for each of the three regions, based on the characteristics of each. Materials and methods. Medical institutions in three regions (St. Petersburg, Leningrad Region and Krasnoyarsk Territory) as sources of medical waste generation were considered taking into account their capacity and specialization. The composition and volumes of waste by class were determined using a calculation method based on indicative waste generation standards. The identification of local technologies for the neutralization of medical waste existing in medical institutions was carried out. The obtained data was processed statistically and displayed on electronic maps for subsequent use in GIS technologies, as well as for the development and justification of a waste management system for medical institutions, taking into account the prospects for the development of healthcare. Results. Based on the analysis of data on medical waste of classes B and C in individual medical institutions, as well as an analysis of the power of existing technologies for neutralizing this waste using GIS technologies, proposals were developed to improve the medical waste management system in three regions. The proposals are aimed at improving the sanitary and epidemiological situation in the regions over a five-year period and take into account the features of the existing transport infrastructure and the requirements of sanitary legislation. Limitations. The model of a medical waste management system using GIS technologies was used only for managing waste of classes B and C. Conclusion. To ensure the safe and environmentally sustainable functioning of the waste management system of classes B and C in the regions, it is necessary to apply an integrated approach based on GIS technologies. This approach should take into account the regional characteristics of the management of the medical waste disposal system and its economic feasibility and take into account the regional characteristics of transport logistics and the prospects for the development of healthcare.

Carbon Emission Effects of Spatially Connected Networks in the Digital Economy： Dynamic Evolution and Mechanism of Action

In the context of the "double carbon" goal and the construction of the "East Counts, West Counts" project, this study investigated the characteristics of the spatial and temporal evolution of the digital economy spatial correlation network, and the effects and mechanisms of carbon emission reduction and carbon rebound effects by selecting data at the level of 254 prefectural-level cities from 2011 to 2021 and using the UCINET software and empirical econometric modeling. The results indicated that： The spatial network of the digital economy represented the development pattern of multiple synergies and had the characteristics of non-equilibrium spatial evolution in geographic regions. Secondly, the spatial network of the digital economy in the sample selection period had a positive contribution to carbon emission reduction, and it led to the carbon rebound effect, which was still valid after the robustness test. Furthermore, the spatial correlation network of the digital economy could reduce carbon emissions by promoting the energy efficiency effect under technological progress and led to the carbon rebound effect. Finally, the empirical results were heterogeneous under the four dimensions of geographic region, administrative level, urban environmental governance objectives, and resource endowment.

Symmetrical Martensite Distribution in Wire Using Cryogenic Cooling

This article presents the results of research on a new combined process involving multi-cycle wire-drawing and subsequent cryogenic cooling after each deformation stage. For theoretical research, modeling in the Deform software was performed. The analysis of temperature fields and the martensitic component in all models showed that for both considered thicknesses, the most effective option is a low deformation velocity and the conduct of a process without heating. The least effective option is to use an increased thickness of the workpiece at an increased deformation velocity and the conduct of a process without of heating to ambient temperature, which acts as a local cooling of the axial zone of the workpiece with an increase in the workpiece thickness. An analysis of laboratory studies on this combined process revealed that in the absence of intermediate heating of a wire between deformation cycles, 100% martensite is formed in the structure. However, if intermediate heating to 20 °C between deformation cycles is carried out, a gradient distribution of martensite can be obtained. And, since the wire has a circular cross-section, in all cases, martensite is distributed symmetrically about the center of the workpiece.

Methodology for Evaluating the Performance of a New Pulse Oximeter Model and Pulse Oximetry Algorithm in Neonates in a Clinical Trial (Exploratory Study)

While evaluating a new domestically produced pulse oximeter model in clinical practice, we discovered a lack of references in Russian-language publications on clinical trial methodologies to assess device reliability and performance.The aim of the study is to create a methodology for conducting a multicenter, prospective, cohort, nonrandomized, controlled clinical trial evaluating a domestic pulse oximeter.Methods. Measurements were performed on 20 preterm infants in the neonatal intensive care unit with a mean birth weight of 2340 [1250; 3125] g and a gestational age of 35 [30; 37] weeks using a new model pulse oximeter simultaneously with the reference monitor. Multiple oxygen saturation measurements of varying duration were taken alternately from the upper and lower limbs, and the number of false desaturation alarms was recorded. Pulse oximeter saturation data were evaluated for correlation with clinical findings.Results. Attachment of sensors to the infant's feet was found to be optimal in terms of ease of use, minimal artifact generation, and minimal interference with routine medical procedures and neonatal care. To reduce motion-induced artifacts and false alarms, the optimal period of SpO₂ monitoring to detect desaturations and bradycardia was determined to be 120 min. Due to the high variability of pulse rate (PR) and saturation in neonates, two-second intervals were determined to be optimal for comparing records from the two monitors. Matching of ECG HR and pulse oximeter PR was required to eliminate artifacts. A mathematical software model required for accelerated analysis of data collected from all sensors during the study was approved.Conclusion. The data analysis supported the proposed methodology for conducting a clinical trial to evaluate the performance and reliability of new pulse oximetry devices.

Towards standarized benchmarks of LLMs in software modeling tasks: a conceptual framework

AbstractThe integration of Large Language Models (LLMs) in software modeling tasks presents both opportunities and challenges. This Expert Voice addresses a significant gap in the evaluation of these models, advocating for the need for standardized benchmarking frameworks. Recognizing the potential variability in prompt strategies, LLM outputs, and solution space, we propose a conceptual framework to assess their quality in software model generation. This framework aims to pave the way for standardization of the benchmarking process, ensuring consistent and objective evaluation of LLMs in software modeling. Our conceptual framework is illustrated using UML class diagrams as a running example.