Model Transformation Research Articles

From SPOD to BANI: Digital Transformation of the Real Estate Organization Business Model

Digital transformation today is an objective reality and a vital need for organizations in all fields of activity. It can be the result of forced circumstances of external conditions (pandemic), as well as an intentional decision of the strategic development set by the company’s management. In both cases, the digital business transformation process provides a multiple increase in the speed, quality, and efficiency of business processes. For real estate, these trends are no exception.The object of research in the article is management business modeling of the activities of real estate organizations. The subject of research is the process of digital transformation of the business model of real estate organization.The purpose of the article is to substantiate the digital business model of real estate organization based on the ecosystem approach in the BANI world.The article justifies the conceptual process of transforming the business models of real estate organizations, based on the evolutionary transition from SPOD to VUCA and the BANI concept of entrepreneurial reality. Each of the presented “worlds” is characterized by differences in management metrics and a different level of technology presence in the activities of organizations. The forced immersion of business in the entrepreneurial BANI world accelerated the processes of digital transformation. The dynamic development and ubiquitous presence of digital technologies requires appropriate adaptation of business models and management approaches. For the conditions of the BANI world, the most relevant is the ecosystem approach, combining complex approaches and platform solutions.

Research on digital intelligence business model based on artificial intelligence in post-epidemic era

PurposeThe 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.Design/methodology/approachThis work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.FindingsThe research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.Originality/valueThe finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

Estonianness in the Making: Transformations of Ethnic Democracy Model and Nationalism in Estonia

Estonian nationalism has undergone a transformation from ‘state-seeking’ to ‘state-led’ since acquiring independence, which has affected the Estonian national identity. Estonia is commonly labelled as an ‘ethnic democracy’; however, we propose a dichotomy between open and closed ethnic democracies. The process of national state-building in Estonia is still going on, with the concept of ‘Estonianness’ consisting of the ‘Finno-Ugric,’ ‘Nordic/Scandinavian,’ and ‘European’ identity structures. These form the basis for an inclusive, or open ethnic democracy. Though Estonianness is primarily defined in cultural and linguistic terms, a newcomer may ascribe oneself to it and become a member of the ethno-civic nation.

Accurate Recognition Method for Rolling Bearing Failure of Mine Hoist in Strong Noise Environment

The operating environment of rolling bearings in mine hoists is complicated, and detecting their faults is hindered by a weak and unstable initial vibration signal. This directly affects the ability to extract pertinent fault features. This paper puts forward an adaptive fault diagnosis method for rolling bearings that combines the Variational Modal Decomposition (VMD) model and Vision Transformer (ViT) deep learning network model. The objective was to address the difficulty of extracting relevant fault features from bearing vibration signals in environments with strong noise levels. First, an improved VMD+ViT model was used to remove the strong noise from the original bearing signal and adaptively classify the fault types; then, the impacts of modal components and encoder numbers on the accuracy of fault diagnosis were explored. Finally, the proposed methodology was validated by applying it to actual rolling bearing fault data, including both open-source and fault test datasets. The research findings indicated that employing a VMD+ViT integrated model consisting of one modal component with the highest Pearson correlation coefficient and eight encoders resulted in high accuracy in diagnosing faults, even in the presence of high levels of noise in the bearing’s vibration signal. The proposed diagnostic method achieved a diagnostic accuracy of over 92.70% on the open-source bearing dataset with strong interference noise and over 98.62% on the fault test dataset. The proposed method exhibited high accuracy and strong robustness, making it suitable for effectively diagnosing and accurately identifying different categories of rolling bearing faults in mine hoists, even in environments with high levels of noise.

Observer-based [formula omitted] control of memristor-based neural networks with unbounded time-varying delays

This work is devoted to developing observer-based H∞ control of memristor-based neural networks with unbounded time-varying delays. A suitable observer is first designed, and then the controller is implemented based on the estimated states. Taking into account the dynamic equation of the MNN and that of the observer error, an augmented closed-loop system is given. By proposing a system solutions-based estimation method, sufficient conditions are obtained to guarantee that the augmented system is globally exponentially stable and satisfies a prescribed H∞ performance level. This approach requires neither model transformation nor the construction of Lyapunov–Krasovskii functionals. In addition, the obtained sufficient conditions contain only a few scalar inequalities, which can be easily addressed by MATLAB. Finally, illustrative simulations are given to test the validity of the theoretical results.

Balancing the scales: labour incorporation and the politics of growth model transformation

ABSTRACT Led by the emerging growth models perspective, research in comparative political economy has recently reintroduced demand drivers of economic growth into the centre of political-economic analysis. While this marks a significant advancement, current scholarship has, so far, focused mainly on explaining the endurance of existing growth models rather than the process of change. To begin addressing this gap, we identify one route to growth model change: the inclusion of organised labour into growth coalitions. Our proposed framework expands the role of growth coalitions in growth models by incorporating insights from the established literature on institutional change. Building on these insights, we distinguish between broad and narrow coalitions based on their scope, composition, and inclusive nature. With this distinction in mind, we argue that when a previously narrow coalition is broadened by incorporating organised labour, it can ‘balance the scales’, i.e. shift the growth model from a purely export-led model into a more balanced one. This shift occurs as labour’s influence on policy promotes wage growth and redistribution which, in turn, fuel wage-based consumption. We demonstrate our theoretical framework through a comparative analysis of the primary case study of Israel and two additional cases of Brazil and Ireland.

Autonomous reliable intelligent control design under condition monitoring mechanism: Applied to hypersonic flight vehicles

For the six-degree of freedom dynamics of hypersonic flight vehicle, an autonomous reliable intelligent controller using online estimation and condition monitoring is designed in this paper. Based on model transformation, the outer-loop trajectory tracking is converted to the inner-loop attitude tracking. According to the aerodynamic model of large flight envelope and the thrust model of combined engine, the original dynamics is transformed into a switched nonlinear form. For each subsystem, neural network and nonlinear observer are employed to deal with aerodynamic uncertainty and external disturbance, while modeling errors are built to design composite update laws. Considering that the statically unstable HFV is prone to large deviation due to mode switching and wind disturbance, the condition monitoring signal with finite-time robust design is introduced to adjust control surfaces. With the average dwell time on the switching signal, the stability of the whole switched system is proved using Lyapunov approach. Simulation studies are performed to show the effectiveness of the design.

Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process

The work presented in this paper focuses on the modeling and implementation of business intelligence processes, specifically how to apply model-driven architecture (MDA) throughout the entire development process of a data warehouse to automatically generate the multidimensional schema. As a result, this work specifies different rules for automating the process of obtaining an online analytical processing (OLAP) cube and implementing it using a collection of metamodels and automatic transformations. The data warehouse relational and OLAP cube models are then created using a model transformation from the conceptual model (class diagram). Finally, the XML file and SQL code are generated for creating the OLAP cubes and relational data warehouse, respectively. Using transformation languages like query-view-transformation (QVT) and Acceleo, all model transformations are performed.

Transformation of the national model of post-war reconstruction of Ukraine according to the European green concept

Methods. The theoretical and methodological basis of the scientific research was the work of domestic and foreign scientists on the issues of Ukraine's adaptation to European standards regarding the country's sustainable development and environmental policy. In order to achieve the goal, the article uses general scientific and special methods: methods of theoretical generalization – to study the process of transformation of the national model of post-war recovery of Ukraine in accordance with the European green concept; the method of general and specific – in the analysis of ambitious and pragmatic models of green recovery of Ukraine; statistical method – when determining the growth of the share of renewable energy sources in the total consumption of energy resources. The results. The article highlights issues related to the compliance of the national policy and strategy of Ukraine with European standards and provides recommendations in the field of ecology, energy and sustainable development of the country, and their financing. It was noted that an important aspect of a sustainable economy is the development of ecologically oriented infrastructure, which includes the following aspects: energy efficiency and renewable energy; ecological transport infrastructure; green construction; water sector. There is considered the possibility of Ukraine to make an energy transition to renewable energy by 2050 under three scenarios of the future of Ukrainian energy: conservative, liberal and revolutionary scenarios. Novelty. A detailed analysis of the green recovery of Ukraine was conducted, which showed that when choosing between ambitious and pragmatic models of the country's post-war recovery, it is important to take into account their main difference. The ambitious model of green country recovery focuses on green development goals, while the pragmatic model only identifies ways to achieve results. Both ambitious and pragmatic models can be comprehensive and sufficient to achieve the respective goal. The article also analysed Ukraine's ability to transition to renewable energy by 2050. Practical value. The results of the conducted research can be useful for business entities and investors who will have a desire to join the green concept of the post-war reconstruction of Ukraine.

Model-driven architecture: generating models from Symfony framework

The web application development industry is constantly growing due to the extensive use of web applications in different devices, most of them run on Android, iOS, and Windows Phone operating systems. However, the development of applications designed for platforms requires more concerns such as code efficiency, interaction with devices, and speed of market penetration. The model-driven approach (MDA) combined with unified modeling language (UML) could provide abstraction and automation for software developers. This paper presents an MDA approach for the development of web applications based on the Symfony framework, UML modeling, model transformation, and then automatic code generation in order to facilitate and accelerate the development of web applications. The first step of this work is to establish the metamodel of Symfony framework and the metamodel of UML class diagram. In the second step, the various transformation rules between the source and target metamodels are first defined. Atlas transformation language (ATL) implements these rules. The result of this transformation is a platform-specific model (PSM) represented by Ecore language. The generated PSM model represents the input model of model-to-code (M2C) transformation for generating the code of web applications. To validate this work, we have implemented a case study.

A Miniaturized Wideband SIR Interdigital Bandpass Filter With High Performance Based on TSV Technology for W-Band Application

In this paper, an ultra-compact wideband stepped impedance resonators (SIR) interdigital bandpass filter (IBPF) is proposed based on through-silicon via (TSV) and three-dimensional integrated circuit (3D IC) technology. SIR structure can achieve higher coupling strength at a small impedance ratio. On this basis, the IBPF is designed by exploiting λ/4 SIR, the proposed filter is realized with compact size and far parasitic passband, and exhibits superior fractional bandwidth and out of band suppression characteristics. Based on the transformation of Chebyshev low-pass circuit model, a seventh-order IBPF centered at 98.5GHz is obtained. An improved method combining TSV technology with coupling coefficient method is proposed, which simplifies the design process and improves the influence of parasitic inductance on the design process. The fractional bandwidth (FBW) of SIR IBPF based on TSV is 40%, the insertion loss is less than 1.3dB, and a reflection of better than 30 dB in the passband. The size of the compact SIR IBPF is only 0.24×0.7mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (0.28 × 0.79 λg <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ).

Current density and thermal propagation of electromagnetic CoFe2O4 and TiO2/C2H6O2 + H2O hybridized Casson nanofluids: A concentrated solar power maximization

The limited availability of fossil fuel, ecosystem consideration and economic factor stimulates interest in alternative energy provision and thermal energy enhancement. Utilization of solar radiation and nanofluids with solid tiny particle provides a platform to optimize renewable solar thermal system performance. Owing to its usages, this study examines thermal transfer and current density of electromagnetic gravity driven Casson hybridized nanofluid flow through partially filled porous media with Ohmic heating. A mixture of cobalt ferrite (CoFe2O4) and titanium dioxide (TiO2) is considered for the nanoparticles thermal propagation in base solvent ethylene-glycol+water (C2H6O2+H2O). A parabolic concentrated solar collector is used for the solar radiation absorption with a continuous energy supply. An invariant transformation of the partial derivative model is obtained using similarity variables. A semi-analytical shifted Chebyshev method coupled with the integrated collocation scheme has been adopted to provide theoretical solutions to the model. The study revealed that concentrated solar power current density is raised as the electric field factor and medium porosity is increased. The fluid velocity is damped while the temperature distribution is enhanced as the nanoparticle volume fraction is boosted. Thus, this investigation will improve the efficiency of thermal engineering products and enhance industrial performance.

Digital Transformation of Incumbent Firms: A Business Model Innovation Perspective

The literature argues that a real digital transformation of firms requires holistic changes of the business model. Despite knowledge about this ambitious goal, understanding of how digital business model transformation can be achieved is still very limited. In this article, we explore how firms achieve digital business model transformation. We apply a case study design to investigate how incumbents have changed their respective business model dimensions during digital transformation. Our findings center on interview data and complementary archival records from 15 cases. We present a framework for digital business model transformation along the dimensions of value proposition, value creation, and value capture. Our results emphasize the importance of a preparatory phase in which the strategic course is set. Furthermore, our findings demonstrate that transforming a company&#x0027;s business model is most effective when a single person, namely the Chief Digital Officer, is responsible. Our findings contribute to the business model literature, by providing a more holistic view on how business model innovation can be utilized during digital transformation.

Optimization of drug scheduling for cancer chemotherapy with considering reducing cumulative drug toxicity

An improved optimal drug scheduling model with considering two control drugs is proposed and the Gauss pseudospectral-based optimization method is studied to decrease the tumor size and drug toxicity in this work. Firstly, the Dexrazoxane drug, which has significant clinical effect to reduce the toxicity of the anticancer drug, is introduced. By analyzing the growth kinetics model of cancer chemotherapy, the toxicity reduction drug is regarded as the second input in the cancer dynamic equations. Correspondingly, the drug scheduling optimization problem with particular optimization goal and necessary constraints is established. Next, a model transformation technique is proposed to reduce the complexity of dynamic equations. With deriving the Gaussian time grid discretization detailly, the Gauss pseudospectral method (GPM)-based cancer chemotherapy drug scheduling algorithm is presented to test the performance of the proposed model within different rates. Finally, the implementation structure of drug scheduling optimization is given in detail. To test and validate the performance of proposed chemotherapy model, extensive simulation results and comparative evaluation are carried out on a specific mathematical model. Simulation results show that the improved optimization model is superior to other literature studies, resulting in the average improvement of performance index by 66.54% and revealing the significant guiding property for cancer chemotherapy.

Decentralized proportional-integral controller based on dynamic decoupling technique using Beckhoff TwinCAT-3.1

An improved technique for the design of decentralized dynamic decoupled proportional-integral (PI) controllers to control many variables of column flotation was developed and implemented in this paper. This work was motivated by challenges when working with multiple inputs and multiple outputs (MIMO) systems that are not controllable by conventional linear feedback controllers. Conventional feedback control design consists of various drawbacks when it comes to complex industrial processes. The introduction of decentralization, decoupling, and many advanced controls design methods overcomes these drawbacks. Hence, the design and implementation of control systems that mitigate stability for MIMO systems are important. The developed closed-loop model of the flotation process is implemented in a real-time platform using TwinCAT 3.1 automation software and CX5020 Beckhoff programmable logic controllers (PLC) through the model transformation technique. The reasons for using the CX5020 as an implementation environment were motivated by the reliability, and is built according to new industry standards, allowing transformation, which makes it more advantageous to be used more than any other PLCs. This is done to validate the effectiveness of the recommended technique and prove its usability for any multivariable system. Comparable numerical results are presented, and they imply that industrial usage of this method is highly recommended.

Study on neutronics modeling with 22.5° model using ANSYS for CFETR

The detailed China Fusion Engineering Test Reactor (CFETR) 22.5° computer aided design (CAD) model is very difficult to convert into Monte Carlo N Particle Transport Code (MCNP). Manually writing MCNP input data is complicated, which is not only time-consuming but also cannot guarantee accuracy. Therefore, in order to improve the efficiency and accuracy of model transformation, modeling with CAD using CATIA is introduced, and MCNP files are converted by ANSYS. This is because ANSYS has a function that converts CAD “stp” format to MCNP input in the geometry section. Meanwhile, ANSYS can also reverse the converted MCNP input file to inspect which module has the problem. Compared with the software platform that can automatically cut, although the CATIA-to-ANSYS method is inferior in terms of automatic operation, it has advantages in accuracy and quickly dealing with error modules. Moreover, it can also perform parametric modeling in CATIA, which facilitates the optimization of the blanket structure. In this paper, the detailed CFETR 22.5° model was developed, and then parametric modeling of the blanket based on CATIA was performed. Finally, a detailed neutronics model is obtained by ANSYS transformation and inspection. Some representative models were initially validated by comparing volume changes before and after conversion. Then, the final neutronics model was used to calculate the nuclear analyses, including the neutron wall loading, fast neutron flux, and nuclear heating on the inboard side. The results show that the volume of the transformed model is basically consistent with the original model, and the error of results is small.

Discrete-Time Adaptive Neural Tracking Control and Its Experiments for Quadrotor Unmanned Aerial Vehicle Systems

For the control of a quadrotor unmanned aerial vehicle, the strong nonlinearities, coupling, and underactuated problem in both positioning and attitude systems of the quadrotor are major challenging issues to be solved. In this article, a discrete-time adaptive dynamic surface control (DSC) scheme for the quadrotor is proposed to obtain a satisfactory tracking performance. The nonlinearities and couplings are overcome by employing the designed robust adaptive DSC nonlinear control method. The underactuated problem is overcome by solving the designed adaptive neural control equations. Also, different from the continuous-time control scheme, the discrete-time control is more suitable for the computer and network control in practicable cases. Furthermore, the digital first-order low-pass filters are constructed to predict the future virtual control signal in the backstepping method, leading to the avoidance of the model transformation problem in the discrete-time backstepping method.

Maintainability enhancement based on uncertain model transformations

Maintainability enhancement based on uncertain model transformations

Taylor, Monique. 2022. China’s Digital Authoritarianism. Politics and Development of Contemporary China. Palgrave Macmillan, Cham. XVII, 169 pp. https://doi.org/10.1007/978-3-031-11252-2

This book examines the problem of modern Chinese digital authoritarianism, as well as the key global process of modern development, covering various areas of public life. The characteristic features of the global and regional trends in the digitalization of society are identified and described, which modernize the task of adapting political regimes to new network conditions both in China and in other authoritarian countries. This, in turn, raises the question of the need for a comprehensive comparative analysis of cases of legitimation of different political regimes in order to develop a package of recommendations for the effective transformation of the modern Chinese political regime. The most difficult scientific problem is, first of all, the definition of deep transformations of social and political reality under the pressure of forced digitalization. Other problems actualize the chosen research topic: the risks and threats of information wars, politicized fakes, attempts to distort historical memory, which can trigger the processes of delegitimization of the political regime. At the same time, digitalization gives political regimes additional prospects in terms of the use of social networks by government bodies, the transformation of communication models of the ruling parties. China’s digital technologies are research topics in political science and international relations that affect the quality and effectiveness of governance. In this regard, time and reflective ways of theorizing about digital technologies in international relations are important. The author focuses on the analysis of the role of technological continuity and changes in China, which today has practically no proven approaches to studying the impact of digitalization and big data on international relations.

Right-censored partially linear regression model with error in variables: application with carotid endarterectomy dataset.

This paper considers a partially linear regression model relating a right-censored response variable to predictors and an extra covariate with measured error. The main problem here is that censorship and measurement error problems need to be solved to estimate the model correctly. In this sense, we propose three modified semiparametric estimators obtained from local polynomial regression, kernel smoothing, and B-spline smoothing methods based on kernel deconvolution approach and synthetic data transformation. Here, kernel deconvolution technique is used to solve the measurement error problem in the model and synthetic data transformation is considered to add the effect of censorship to the estimation procedure, which is a very common method in the literature. The performances of the introduced estimators are compared in the detailed Monte-Carlo simulation study. In addition, Carotid endarterectomy data is used as real-world data example and results are presented. According to the results, it is seen that the deconvoluted local polynomial method gives more qualified estimates than other two methods.