Model Of Digital System Research Articles

Does effectiveness of digital accounting system intensify sustainable business model innovation with mediating role of digital business ecosystem?

The current research aims to unveil the interconnection between effectiveness of digital accounting information system (EDAIS) and sustainable business model innovation (SBMI). In particular, the study investigates the mediating function of digital business ecosystem (DBE) between EDAIS and SBMI. In this regard, this study confirms and establishes the relationships between EDAIS, DBE, and SBMI by using a sequential exploratory strategy that combines literature review and qualitative interviews, together with a quantitative survey of 723 small and medium enterprises (SMEs). The results analysis indicated that EDAIS had a positive impact on SBMI. Furthermore, it was shown that DBE had a role in partially mediating the relationship between EDAIS and SBMI. Therefore, it is recommended that practitioners adopt digital transformation and harness national policies, in order to improve their company's use of digital technology in accounting. Additionally, policymakers and practitioners can use this investigation to enhance their comprehension of the governance of DBE and to elucidate strategies, procedures, and management for DBE in order to establish and attain SBMI in the digital environment.

Geo-spatial analyses of meandering rivers, assessing past and future impacts on bank landforms and LULC changes

ABSTRACT Morphological investigation of rivers is difficult but is one of the vital topics for the management of highly meandering river systems. The study employs a geographical information system (GIS) to analyse 32 years of Barak River data, addressing challenges in quantifying the morphology of meandering rivers. Earth observatory data from 1990 to 2022 track channel bank shifts and Land Use/Land Cover (LULC) alterations. Although the digital shoreline analysis system (DSAS) model identified long-term bank line migration analysis of shorelines, its use is very new for rivers, especially in terms of the meandering of rivers. Conversely, research on long-term meandering river morphology in the Barak River channel has not been conducted despite evident land-use changes. Using DSAS for bank positions and cellular Automata -Markov (CA -Markov) models for LULC, future projections until 2043 reveal ongoing Barak River bank shifts and significant LULC pattern alterations. The findings of the research were validated through root mean square error (RMSE), Student's t-test, chi-square, and the kappa coefficient. Forecasts indicate that rapid urbanization impacts river morphology. The methodology is crucial for managing highly meandering rivers, particularly in contexts involving vulnerable river systems.

A model for sustainable development: Advancing digital food retailing

The technological revolution has driven food retail towards self-service technologies (SSTs). The supermarket concept thrived due to consumer convenience and direct food access. This qualitative study explored the modernization of food retail through new technologies, focusing on Canadian stakeholders’ perceptions. Using a grounded theory approach, it aimed to create a sustainable digital food system model addressing social and moral food access aspects. Findings revealed that digitalization in food retail is driven by economic motives and stakeholders’ desire for collaboration and partnership to support food access.

Integrating a multi-variable scenario with Attention-LSTM model to forecast long-term coastal beach erosion

Beach erosion is an adverse impact of climate change and human development activities. Effective beach management necessitates integrating natural and anthropogenic factors to address future erosion trends, while most current prediction models focus only on natural factors, which may provide an incomplete and potentially inaccurate representation of erosion dynamics. This study enhances prediction methods by integrating both natural and anthropogenic factors, thereby enhancing the accuracy and reliability of erosion projections. By extracting historical shorelines through CoastSat model from 1986 to 2020, we develop multivariable scenarios with Attention-LSTM model to predict the regional impacts of natural and anthropogenic factors on erosion to sandy beaches along the typical shoreline of Shenzhen in China. Results reveal that Shenzhen's beaches experienced erosion up to 12 m over the past 35 years. Here we project a decrease in the mean erosion rate of the beaches, identifying population growth (21.0 %) as the main controlling factor before the mid-century in a range of scenarios. We find that Attention-LSTM multi-model ensemble approach can provide overall improved accuracy and reliability over a wide range of beach erosion compared to scenario prediction model of Attention-LSTM and statistical model of Digital Shoreline Analysis System (DSAS), yielding an average uncertainty of 10.99 compared to 13.29. These insights reveal policies to safeguard beaches because of the rising demand for beaches due to human factors, coupled with decreased impervious surfaces through ecological conservation, lead to mitigation for beach erosion. Accurate forecasts empower policymakers to implement effective coastal management strategies, safeguard resources, and mitigate erosion's adverse effects. Our study offers finely-tuned predictions of coastal erosion, providing crucial insights for future coastal conservation efforts and climate change adaptation along the shoreline, and serving as a foundation for further research aimed at understanding the evolving environmental impacts of beach erosion in Shenzhen.

Research on the Impact of Digitalization on Bank Performance Based on BP Neural Network

With the promotion and development of digital finance, the degree of digitalization has an increasingly significant impact on the banking business, which cannot be ignored in the operation of commercial banks. Therefore, establishing a digitalization bank profitability system model is of great significance for the sustainable development of banks and digital finance. This article selects 6 Chinese state-owned banks from 57 listed banks in the A+H stock market as samples, constructs a digital indicator system and evaluation model for banks through the literature review method, and uses simulation training to explore the effectiveness of BP neural network in evaluating the impact of digitalization on bank profitability. The aim is to provide a reference for the evaluation of financial statement information of other banks and other factors affecting bank digitalization. The innovation of the article lies in the innovative use of the entropy weight coefficient of variation method to establish a digital evaluation system model, which utilizes the data itself to objectively establish an evaluation system, incorporate the established digital system into the black box model of the BP neural network model to study the impact of changes in digitalization on banking operations.

Geometric-Optical Model of Digital Holographic Particle Recording System and Features of Its Application

The paper proposes an equivalent optical scheme of an in-line digital holographic system for particle recording and a mathematical model that establishes a one-to-one correspondence between the dimensional and spatial parameters of a digital holographic image of a particle and the imaged particle itself. The values of the model coefficients used to determine the real size and longitudinal coordinate of a particle according to its holographic image are found by calibration. The model was tested in field and laboratory conditions to calibrate a submersible digital holographic camera designed to study plankton in its habitat. It was shown that four calibration measurements are sufficient enough to determine the model coefficients, and the developed design of the submersible digital holographic camera makes it possible to perform these measurements during the recording of each hologram. In addition, this neither requires data on the refractive index of the medium with particles nor on the parameters of the optical elements of the scheme. The paper presents the results of marine experiments in the Kara Sea and the Laptev Sea, as well as in fresh water in laboratory conditions and in Lake Baikal. The error in measuring the particle size in seawater without the use of the model is 53.8%, while the error in determining their longitudinal coordinates is 79.3%. In fresh water, the same errors were 59% and 54.5%, respectively. The error in determining the position of a particle with the use of the designed mathematical model does not exceed 1.5%, and the error in determining the size is 4.8%. The model is sensitive to changes in the optical properties of the medium, so it is necessary to perform calibration in each water area, and one calibration is quite sufficient within the same water area. At the same time, the developed design of the submersible holographic camera allows, if necessary, calibration at each holographing of the medium volume with particles.

A Digital Twin-Based Approach for the Optimization of Floor-Ball Manufacturing

The increasing complexity of products and manufacturing processes, combined with the constantly advancing technological integration of the manufacturing sector, raised new challenges for world-class industries to optimize time-to-market, resources, and cost. Simulation, as an essential Industry 4.0 enabling technology, allows one to emulate the steps of a manufacturing process, thereby achieving significant improvements in all the product and process development phases. A simulation process can be implemented and improved by creating the Digital Twin of the manufacturing system, which can be realized on a single-line scale or extended to the whole factory. The Digital Twin merges physics-based system modeling and real-time process data to generate a virtual copy of an observable object to reduce and optimize the extensive time and cost of physical design, prototyping, commissioning, reconfiguration, and maintenance. This study aims to investigate how the implementation of digital twin technology can help optimize the balance between power consumption and productivity, taking into account existing barriers and limitations. By following this outline, this study shows the design and development of a digital twin for a floor-ball manufacturing line present in the Smart Factory of Ostschweizer Fachhochschule (Switzerland). The entire production process is reproduced with Siemens Technomatix Plant Simulation software 2201, and data connection and processing are handled by a tailored toolchain consisting of an agent, a database, Python packages, and the COM interface from Tecnomatix. This toolchain feeds the digital twin with data from the physical operating environment. In particular, this study compares direct power measurements with the ones expected by the digital twin to assess digital model accuracy.

Trustworthy Digital Representations of Analog Information—An Application-Guided Analysis of a Fundamental Theoretical Problem in Digital Twinning

This article compares two methods of algorithmically processing bandlimited time-continuous signals in light of the general problem of finding “suitable” representations of analog information on digital hardware. Albeit abstract, we argue that this problem is fundamental in digital twinning, a signal-processing paradigm the upcoming 6G communication-technology standard relies on heavily. Using computable analysis, we formalize a general framework of machine-readable descriptions for representing analytic objects on Turing machines. Subsequently, we apply this framework to sampling and interpolation theory, providing a thoroughly formalized method for digitally processing the information carried by bandlimited analog signals. We investigate discrete-time descriptions, which form the implicit quasi-standard in digital signal processing, and establish continuous-time descriptions that take the signal’s continuous-time behavior into account. Motivated by an exemplary application of digital twinning, we analyze a textbook model of digital communication systems accordingly. We show that technologically fundamental properties, such as a signal’s (Banach-space) norm, can be computed from continuous-time, but not from discrete-time descriptions of the signal. Given the high trustworthiness requirements within 6G, e.g., employed software must satisfy assessment criteria in a provable manner, we conclude that the problem of “trustworthy” digital representations of analog information is indeed essential to near-future information technology.

Research on digital twin modeling and monitoring technology for smoke alarm calibration system

Aiming at the problems of backward calibration method of smoke alarm, low production efficiency and difficult real-time monitoring, a digital twin system modeling and monitoring method of smoke alarm calibration is proposed. First, through the analysis of smoke alarm calibration requirements, the overall framework design of the digital twin calibration system for smoke alarm is proposed, and then the twin model of smoke box is constructed by running the digital twin five-dimensional model. The physical smoke box, geometric model, physical model, rule model and behavior model are introduced in detail; Then the communication system architecture, data acquisition and data mapping are used to construct the twin data model; Finally, the feasibility was verified by the calibration system of an enterprise. Through the system, the qualified rate of smoke alarm calibration was increased from 98 to 99.6%, and the repair rate of defective products was reduced by 1.6%.

Method for Executing Digital System Models and Digital Twins at Scale to Enrich Fleet Health Management

The digitization of the aviation industry brings the promise of increased transparency into the engineering design across aircraft lifecycles. With an increased focus on Model-Based Engineering, design engineers are constructing interoperable, standardized simulation models which can be leveraged across the Digital Thread. This advancement presents an opportunity to improve health management and prognostics by directly comparing these models against in-service data. This paper proposes a method for leveraging engineering Digital System Models and Digital Twins at-scale to facilitate and enrich health management activities. Supporting considerations include specifying model standards and ingesting fleet-level data using cloud computing.

Retracted: Digital Modeling System for Dynamic Nonlinear Systems of Power Equipment in Digital Grids and 5G

Retracted: Digital Modeling System for Dynamic Nonlinear Systems of Power Equipment in Digital Grids and 5G

Validation of Digital System Models: A Framework and SysML Profile for Model‐Based Systems Engineering

AbstractDigital Engineering (DE) and Model‐Based Systems Engineering (MBSE) are transforming existing acquisition processes. Little extant research exists regarding validation of digital system models. In the traditional “design‐build‐test” method, stakeholder requirements validation occurs near the end of development. However, DE is described as a “model‐analyze‐build” approach where validation is required earlier in the lifecycle to refine and add digital elements to the authoritative source of truth. This paper describes a framework for model‐based design reviews (MBDR) and extends previous work by Hecht and Chen. Validation use case development is emphasized to capture both the intent, the “why,” and the evidence, the “what,” required to enter or exit a preliminary design review (PDR). Model requirements are derived from model use cases, and validation test cases enable automated and manual assessment of quality, completeness, and consistency. The framework is successfully prototyped on a small unmanned airborne system (sUAS) model created for a graduate course PDR. There appears to be wide interest across the U.S. Air Force for a similar framework.

Data generation for digital simulators of metallurgical process operators

The article deals with the formation of model implementations of time series of data (based on in-situ data) of controlled and uncontrolled impacts in simulator-training and digital modeling systems. Such simulators are becoming increasingly widespread due to the development of information and computer technologies, automated research systems, training systems, digital modeling technologies (APM modeling), as well as digital counterparts and advanced control systems. The formed implementations of impacts can characterize situations of normal process flow, emergency and pre-emergency states, or specific representative situations for training operators and technological personnel, software testing, research and tuning of algorithms and search for optimal control actions. Using examples from the metallurgical industry, the possibility of forming several interrelated impacts based on models of nonlinear dynamics and multivariate dynamic databases is shown. The Lorentz system describing the thermal convection of a fluid medium is considered as a model of the impacts formation. The model parameters for the low- and high-frequency components are determined separately, by processing in-situ data. Next, a training sample is formed using normalization and relay-exponential smoothing operations. The implementations of the actions are formed taking into account the mutual correlation of data based on models of chemical dynamics and are adjusted to the specified properties on a limited sample of a given volume with the required accuracy using a generator in the form of a closed dynamic system. The generator in form of a closed dynamic system is built on the basis of a multidimensional generating autoregressive model with adjustable coefficients. An example of the formation of data series on technological parameters of a blast furnace (the degree of wear of the furnace lining, temperature sensor readings and heat flux density) is shown.

A Digital System Model for Healthcare Management in Thai Supply Chain

The paper is a survey study. The paper title is a digital system model for healthcare management in Thai supply chain. The paper finding has been found that a digital system model for healthcare management in Thai supply chain comprises six main elements, namely, manufacturer, Purchasers, Healthcare provider, customer and satisfaction. All elements are connected with digital. A sample group are ten experts. The research tool was evaluation form to evaluate a digital system model for healthcare management in Thai supply chain. The data is analysed by arithmetic means and standardized deviations. The evaluation results a digital system model for healthcare management in Thai supply chain from ten experts was appropriate in a good level which mean that a digital system model for healthcare management in Thai supply chain can be appropriately applied in actual work settings.

Research on digital twin technology of large-scale offshore wind power flexible direct transmission system

With the rapid development of wind power technology, offshore wind power transmission technology has gradually matured. Combined with the first large-scale offshore wind power flexible DC transmission system in China, this paper builds a digital twin system that is close to the actual system. The article first introduces the origin and definition of digital win technology and gives the five-dimensional model of the digital twin. Then, it focuses on the technical realization of the offshore wind power digital twin system, including the five-dimensional model of the offshore wind power digital twin system. The key technologies in the advanced application of the twin system - real-time simulation technology and 3D holographic visual display technology are introduced, and their effects are shown. The realization of the digital twin technology of the large-scale offshore wind power flexible DC transmission system provides more valuable information for the operation, management, scheduling, and decision-making of the offshore wind power flexible direct transmission system.

Digital System Model for Asset Management in the Universities in Thai Supply Chain

The article was conducted to develop and to evaluate digital system model for asset management in the universities in thai supply chain. A samples group in the research study consisted of ten experts consisted of five experts on supply chain management, five experts on digital, Data were analysed by arithmetic mean and standard deviation. The article findings model six elements namely main components, Suppliers , Universities , customers, satisfaction, feedback . The assessment digital system model for asset management in the universities in thai supply chain using Black-Box technique and The results from experts agreement digital system model for asset management in the universities in thai supply chain was a high level. The model could be used to develop digital asset in the universities.

A Digital System Model for Online Driver's License for Department of Land Transport in Thai Supply Chain

The purpose of paper study were to study a digital system model for online driver’s license department of land transport in Thai supply chain and evaluation of the model . The sample group in this study consisted of ten experts using purposive sampling. Data were analysed by arithmetic mean and standard deviation . The research findings model six elements namely main components, Supplier, Department of land transport, Finished person ,Customers satisfaction and Return. The ten experts agree that a digital system model for online driver’s license department of land transport in Thai supply chain was high suitability which mean that The model may be appropriately applied in actual work settings.

A Digital System Model for Online Driver's License for Department of Land Transport in Thai Supply Chain

The purpose of paper study were to study a digital system model for online driver’s license department of land transport in Thai supply chain and evaluation of the model . The sample group in this study consisted of ten experts using purposive sampling. Data were analysed by arithmetic mean and standard deviation. The research findings model six elements namely main components, Supplier, Department of land transport, Finished person ,Customers satisfaction and Return. The ten experts agree that a digital system model for online driver’s license department of land transport in Thai supply chain was high suitability which mean that The model may be appropriately applied in actual work settings.

Coupling of adjoint-based Markov/CCMT predictive analytics with data assimilation for real-time risk scenario forecasting of industrial digital process control systems

Risk early detection and controls are critical to avoid unforeseen accidents or incidents across safety-critical industries especially in a digitalization context. Using the sequential Monte Carlo particle filter method, an adjoint-based Markov/Cell-to-Cell Mapping Technique (Markov/CCMT) predictive analytics coupling with data assimilation is proposed in the paper for dynamic risk and reliability scenario modeling of industrial digital process control systems. The particle filter-based data assimilation method is developed with a sequential importance sampling with resampling scheme for extended system state estimation and dynamic reshaping of system state-space model. Then the Markov/CCMT predictive analytics models are dynamically constructed using an equal-weight quadrature scheme for approximating the probabilistic cell-to-cell mapping relations that reflect the possible system state transitions on the discretized state-space model in real time. The adjoint-based Markov/CCMT modeling for risk scenario forecasting is demonstrated on a digital U-shaped Tube Steam Generator (UTSG) water level control system in nuclear power plants. The demonstration results show that super real-time and consistent predictions can be obtained within the adjoint-based Markov/CCMT predictive analytics framework. Multi-step time-series forecasting towards the identification of system-level degradation states and risk-significant scenarios evolution can also be envisioned when a blended state merging and pruning strategy is adopted in deep model search. The proposed Markov/CCMT predictive analytics is able to deliver proactive insights to intelligent operation and maintenance of complex safety-critical engineering systems.

Sociotechnical factors of sustainable digital health systems: A system dynamics model

BackgroundThe introduction of digital health technology in a healthcare facility results in emergent and recursive interactions between new technology and existing social systems, technologies, and operating environments. ObjectivesThe study aims at developing a sociotechnical system dynamics model of digital health systems to assess the influence of sociotechnical factors on the sustainable use of an electronic Health Information Management System (eHMIS). MethodsA total of 40 face-to-face interviews in 18 healthcare facilities and two separate sessions of focus group discussions were conducted to study eHMIS implementation in Ethiopia. A system dynamics modelling of digital health systems implementation is developed, tested and verified with a case of eHMIS implementation in Ethiopia. ResultsThe long-term sustainability of the digital health system requires acceptance of technology, improved information quality to make appropriate decisions and better end-user satisfaction. The ‘individuals’ intention to use’ drives technology acceptance in the early years of the eHMIS use and social factors in the later stage. Besides, the role of technology to improve work performance determines the level of users’ satisfaction. The effort of improving ‘information quality’ is strongly influenced by the quality systems, i.e., reliable, easy to use, and capable to meet end-user requirements. ConclusionsThe system's acceptance was improved through effective training and communication, whereas the ‘information quality’ was enhanced through ‘system quality’ and users’ satisfaction. The ability of technology to improve work performance and reduce the burden on end-users has increased the satisfaction of end-users.