Structural Analysis Model Research Articles

Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks

The intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to conventional methods in the schematic design phase of reinforced concrete (RC) shear wall structures. However, for the following reasons, it is challenging to apply GAN-based approaches in the industry and to integrate them into the structural design process. (1) The data form of GAN-based methods is heterogeneous from that of the widely used computer-aided design (CAD) methods, and (2) GAN-based methods have high requirements on the hardware and software environment of the user’s computer. As a result, this study proposes an integrated schematic design method for RC shear wall structures, providing a workable GAN application strategy. Specifically, (1) a preprocessing method of architectural CAD drawings is proposed to connect the GAN with the upstream architectural design; (2) a user-friendly cloud design platform is built to reduce the requirements of the user’s local computer environment; and (3) a heterogeneous data transformation method and a parametric modeling procedure are proposed to automatically establish a structural analysis model based on GAN’s design, facilitating downstream detailed design tasks. The proposed method makes it possible for the entire schematic design phase of RC shear wall structures to be intelligent and automated. A case study reveals that the proposed method has a heterogeneous data transformation accuracy of 97.3% and is capable of generating shear wall layout designs similar to the designs of a competent engineer, with 225 times higher efficiency.

Pathos in the structure of Laz Ekwueme’s Choral Music: Hombe

Studies have covered analysis in Western and African compositions to include a detailed description of the arrangement of every segment of the music. However, less structural analysis has ventured into the pathos of the arrangement of the musical segments. Engaging in the pathos of the structure of Laz Ekwueme’s choral music (Hombe) will bring to limelight how musical structure enhances emotions and psychological feelings. Methodology relies on analysing the musical elements explored in the composition and close score reading of Hombe using structural analysis model. The result shows that Ekwueme employed the Western four-part chorus arrangement as an ornamental device to establishing the diverse African music elements such as repetition of thematic idea in all parts for emphasis, syncopation, varied tempo and shifting accents and tonality thereby enhancing varied moments of emotions, affects and excitement. The paper concludes that the arrangement of different segments of Hombe created moments of extraordinary pathos evoking different emotions and psychological feelings. Musical structure is thus a compositional device with the power to evoke feelings thereby creating a characteristic pattern of a musical style.

Links between ease of use, perceived usefulness and attitudes towards technology in older people in university: A structural equation modelling approach

Technological resources have the potential to improve the quality of life in a context in which social pressure for the use of these tools is increasing. In this sense, the adoption of technological resources by the elderly is a highly complex issue because numerous and varied factors are involved. Precisely for this reason, this study aims to analyze the effects that exist between a series of dimensions related to the perception of older people regarding the ease of use, the perceived usefulness of technological tools, attitudes towards technology and their intention to use them in everyday life. To do this, 415 adults (M = 66.27 years) enrolled in a program at the University of Experience in the Spanish context completed an online questionnaire. The application of a Structural Equations Model for data analysis highlights that the perceived ease of use of the technology has a positive effect on the perceived usefulness of these resources. Similarly, an indirect effect of the perceived usefulness of technology on the intention to use these resources is observed through the manifestation of positive attitudes towards the use of digital tools.

Contextualizing focal structure analysis in social networks.

Focal structures are key sets of individuals who may be responsible for coordinating events, protests, or leading citizen engagement efforts on social media networks. Discovering focal structures that are able to promote online social campaigns is important but complex. Unlike influential individuals, focal structures can affect large-scale complex social processes. In our prior work, we applied a greedy algorithm and bi-level decomposition optimization solution to identify focal structures in social media networks. However, the outcomes lacked a contextual representation of the focal structures that affected interpretability. In this research, we present a novel contextual focal structure analysis (CFSA) model to enhance the discovery and the interpretability of the focal structures to provide the context in terms of the content shared by the focal structures through their communication network. The model utilizes multiplex networks, where one layer is the user network based on mentions, replies, friends, and followers, and the second layer is the hashtag co-occurrence network. The two layers have interconnections based on the user hashtag relations. The model's performance was evaluated on various real-world datasets from Twitter related to COVID-19, the Trump vaccine hashtag, and the Black Lives Matter (BLM) social movement during the 2020–2021 time. The model discovered contextual focal structures (CFS) sets revealed the context regarding individuals’ interests. We then evaluated the model's efficacy using various network structural measures such as the modularity method, network stability, and average clustering coefficient to measure the influence of the CFS sets in the network. Ranking correlation coefficient (RCC) was used to conduct the comparative evaluation with real-world scenarios to find the correlated solutions.

МЕТОДОЛОГИЧЕСКИЕ АСПЕКТЫ ПРОЕКТИРОВАНИЯ ЦИФРОВОЙ МОДЕЛИ ПРОЦЕССА ДВУСТОРОННЕЙ ТОРЦЕШЛИФОВАЛЬНОЙ ОБРАБОТКИ

The paper is devoted to the development of methodological foundations of digital models of two-sided face grinding treatment. The study objective is further increase in the effectiveness of work preparation of two-sided face grinding in the conditions of automated and digital manufacture. At the present stage of the development of mechanical engineering and computerized manufacture the technological parameters of adjustment and cutting modes of metalworking systems should be determined not by reference data, but as a result of simulation modeling of treatment processes taking into account all actual technological factors of influence. The problem to which the paper is devoted is the search for solutions to the problems of ensuring the correctness of mathematical and computer models being developed, adequate consideration of dominant factors, correct representation in the digital form of treatment process of patterns, relationships and constraints taking place based on the methods of structural parametric analysis and simulation modeling. These problems can be solved only on the basis of a systematic approach to the treatment and the development of methodological foundations for creating its digital model, which is the subject of research in the presented paper in relation to two-sided face treatment (FT). The following things are proposed: an algorithm of structural and parametric FT design, a structural and functional model of workpiece forming, objects and connections of technological interaction in FT, which together are the methodological foundations for the virtual FT presentation and have signs of scientific novelty. The results of virtual FT of cylindrical rollers in production conditions and the technical settings of the machine found on the basis of the stated methodological recommendations show that the required values of the dominant shape errors and the relative position of the treated surfaces are provided within the specified constrains. Conclusions: the provisions given in the paper and the model environment can be used in the development of an automated system for technological FT preparation in the conditions of digital production.

Modeling the predictors of students’ entrepreneurial intentions: The case of a peripheral European region

This study analyzes the predictive factors influencing the entrepreneurial intentions of students at higher education institutions (HEIs) in a peripheral European region. The study includes a sample of 594 students and uses structural equation models for data analysis. The results show that the attitude to behavior and perceived behavioral control positively influence entrepreneurial intention. Furthermore, subjective norms positively impact the attitude to behavior and perceived behavioral control. ‘Closer’ valuation (i.e., of family, friends, etc) influences attitude to behavior and social valuation positively impacts subjective norms. This research contributes to the literature on entrepreneurial intention as it complements the Theory of Planned Behavior (TPB) with two environmental factors: closer valuation and social valuation. This is important because it provides evidence of whether the environment of the country in question influences entrepreneurial intention and indicates the need for investment in entrepreneurship education. Consequently, the study contributes to the literature by identifying educational factors that may influence students to become entrepreneurs in a peripheral European region. Further, this paper tests the relationship between the attitude towards behavior and subjective norms, perceived behavioral control and subjective norms, something not proposed in the original TPB model.

Factors Influencing Chinese Consumers’ Desire to Use E-payment in Thailand

As Corona virus pandemic has become a major driving force of seismic shift in how people shop and pay all over the world. These new consumer preferences of e-Payment are here to stay and will continue to shape the next normal for everyone involved in this whole new ecosystem for the years to come. Therefore all key stakeholders need to understand what factors influence and shape this changing market dynamics and shifting consumer expectations for these new e-Payment trends in order to remain competitive and thrive. Since Thailand has become tourist destination of Chinese. Consequently, e-Payment is becoming popular in recent years especially during Covid-19 pandemic. The purpose of this research is study of Factors influencing Chinese consumers’ desire to use e-Payment in Thailand. These factors are Benefits (BN), Trust & Security (TS), User friendly (UF), Technology (TN), Popularity (PP), Culture (CU), Government Policy (GP), Social Pressure (SP), Pop Culture (PC), Product value (PD) and e-Payment behavior (EP). 400 sample were collected using electronic questionnaire through social media such as Facebook, WeChat and Line. We used second-order Structural Equation Models (SEM) for data analysis. The result shows that RMSEA is .052 (<.06) which strongly indicates a “close fit” and the Goodness of Fit Index (GFI) value is .900, the model seems to fit well according to the descriptive measures of fit. More importantly, Trust & Security (TS) and second-order latent variable called Product value (PD) which represents User friendly (UF) and Technological aspects (TN) of e-Payment system seem to have significant effects on customer desire to use e-Payment due to their p-values are both less than .05. That means if e-Payment operators can provide highly-secure, high-tech, and user-friendly e-Payment system that can be trusted, people will be more likely to switch to use e-Payment to replace cards and cash any day. The results found in this research will help all key stakeholders—businesses, merchants, issuers and regulators alike—shape their strategy and identify critical technologies, rules and regulations to best position their organization for growth and support a rapid evolution of e-Payment methods in the new normal.

Role of Peer Influences on Young Consumers’ Green Apparel Perceptions

The study explores the young consumers’ past environmental behaviour and peer influences in shaping green apparel’s perceived benefits in India. Data was corralled using convenience sampling method and partial least square structural equation modelling for the statistical analysis. The results show that past environmental behaviour and green peer influences significantly and positively impact young consumers’ green apparel perceived benefits for pro-environmental behaviour. The specific indirect effect, that is, past environmental behaviour↓green peer influence↓green apparel perceived benefits has a low β-coefficient (0.197) but the cumulative effect was stellar ( β-coefficient = 0.744). Additionally, the prediction power of the proposed conceptual model was 59.2% (adjusted R2 = 0.592). The results were effusive of the fact that past environmental behaviour has the highest influence in shaping young consumers’ green apparel perceived benefits and the cumulative effect with green peer influences, enhances the relationship further. The moderation effect of gender was also explored and confirmed gender neutrality. The study has fructifying implications for green marketers and researchers which would help achieve motives for a sustainable green apparel industry.

ToxSTAR: drug-induced liver injury prediction tool for the web environment.

Drug-induced liver injury (DILI) is a challenging endpoint in predictive toxicology because of the complex reactive metabolites that cause liver damage and the wide range of mechanisms involved in the development of the disease. ToxSTAR provides structural similarity-based DILI analysis and in-house DILI prediction models that predict four DILI subtypes (cholestasis, cirrhosis, hepatitis and steatosis) based on drug and drug metabolite molecules. ToxSTAR is freely available at https://toxstar.kitox.re.kr/. Supplementary data are available at Bioinformatics online.

The relationship between distributed leadership and teacher innovativeness: Mediating roles of teacher autonomy and professional collaboration.

Principals’ distributed leadership plays a critical role in teacher innovativeness; however, research evidence regarding the relationship between them is limited. This study aims at examining the effect of distributed leadership on teacher innovativeness as well as the mediating roles of teacher autonomy and professional collaboration. Using the data of 132,376 teachers derived from the 2018 Teaching and Learning International Survey (TALIS), the study applied a structural equation model (SEM) for analysis. The results revealed that distributed leadership had positive direct effects on teacher innovativeness, teacher autonomy, and professional collaboration. Meanwhile, teacher autonomy and professional collaboration significantly mediated the effect of distributed leadership on teacher innovativeness, respectively. Practical implications are discussed, school leaders are expected to adopt distributed leadership style and establish a supportive school environment, and individual teachers are supposed to cultivate a culture of collectivism and make effective use of autonomy in their teaching innovation.

Analysis of China's regional differences in water consumption based on spatial structural decomposition analysis model

Analyzing the factors that affect the spatial differences in production water consumption in China is necessary to implement its most stringent water resource management system effectively. Based on the input-output tables of 31 provinces and the water-consumption data of provinces by sectors in 2017, the water consumption-economy input-output tables of 31 provinces are constructed. The spatial structural decomposition analysis method is used to analyze the impact of technology level, economic scale, and regional characteristics on spatial differences in production water consumption. The final demand effect is then decomposed into final demand sectoral structural effect, final demand distribution structure effect, population-scale effect, and consumption-level effect. The results show that production water consumption depends on the economic scale and regional characteristics. Xinjiang, Jiangsu, Guangdong, Heilongjiang, and most provinces in the central region use more production water than the average level, while those in the Beijing-Tianjin region and most in the North-west region use less than average. The decomposition results show that the technical and the final demand effects are the main factors for the spatial differences. The impact of population-scale and consumption-level contribute the most to the final demand effect.

A rate-dependent constitutive model of piezoelectric thermoelasticity and structural thermo-electromechanical responses analysis to multilayered laminated piezoelectric smart composites

Thermo-electromechanical coupling analysis at micro/nano-seconds appears to be particularly important, where strain and electric relaxation effects will increase significantly in such case. So far, although temperature-rate-dependent theory of piezoelectric thermoelasticity has been historically proposed, it may be no longer hold anymore as relaxation effects both in electrical and strain fields have not been fully considered yet. This work mainly contributes to constitutive modeling of a novel rate-dependent piezoelectric thermoelasticity by considering time-derivatives terms of the elastic strain, relative temperature, and electric intensity associated with related relaxation time parameters. Constitutive and field equations are strictly derived via extended thermodynamics. Newly developed theoretical model is applied to analyze structural thermo-electromechanical responses of multilayered laminated piezoelectric smart composites accounting for contact imperfection and material parameters via a semi-analytical integrated transformation technique. Dimensionless results reveal that the properly selecting thermal/stain/electric relaxation time parameter or considering non-idealized boundary conditions at interface of multilayered laminated piezoelectric smart composites will maximally enhance the electric energy harvesting, realize the displacement control, and improve the harmful stress isolation.

The Interplay of Social Influence, Financial Literacy, and Saving Behaviour among Saudi Youth and the Moderating Effect of Self-Control

This study examined the impact of social influence, i.e., parents and peers, on the level of financial literacy among Saudi young adults (students). It also assessed the effect of financial literacy on the development of saving behaviour and the role of self-control as a moderator in the relationship between financial literacy and saving behaviour among the same respondents. The study’s sample included 270 respondents (male and female) from an applied college affiliated with King Faisal University. The study employed partial least squares structural equation modelling (PLS-SEM) for data analysis and interpretation. Some intriguing findings were generated. It was discovered that the influence of both parents and peers can positively predict financial literacy. Furthermore, financial literacy can positively impact young people’s saving habits. One surprising finding was that self-control negatively moderated the relationship between financial literacy and saving behaviour. Self-control was found to dampen the ties between Saudi young people’s financial literacy and saving behaviour.

Basic industries of Russia’s industrial regions: The image of the future

Industrialisation remains the major factor of development in the era of radical changes. Its drivers – advanced digital production technologies – are transforming the entire industrial and spatial landscape. Industrial regions take a special role in these transformations. The research aims to identify trends in the development of basic industries in industrial regions and work out a method to form their new technological image. Methodologically, the study relies on the institutional theory, theories of sustainable and longterm technical and economic development; applies methods of comparative, statistical, structural analysis and neural network modelling. Considering the case of the Ural metal industries, the study reveals the main trends of development and possibilities of forming the image of future of the basic industries of Russia’s industrial regions, as well as specifies the factors that modify these trends under the New Normal. Due to institutional and technological transformations, the Russian metal industries have achieved impregnable positions in the world market. The paper substantiates the changes in the development of the basic industries linked with the formation of Industry 5.0 as the new management paradigm, which assigns priority to the ESG factors. The research demonstrates that an indispensable condition for the successful functioning of companies is the ability to cooperate and agree on decisions. The findings confirm that modernised metal and other basic industries through integrating green, digital and behavioural economy will not only maintain, but are likely to increase their importance in the economy of industrial regions.

Defining cost standard and new algorithm for economic leakage level components in water loss management

Methods and tools used to reduce leakage in distribution systems are often time consuming and costly and require special requirements. Therefore, cost-benefit analysis is very important for basic reduction methods applied in water loss management. In this study, cost and benefit analysis standards were developed for basic methods such as pressure management, number of teams, and pipe rehabilitation and active leakage control, in managing leakages. Moreover, a new cost algorithmic structure was developed and the economically recoverable water amount was determined by applying calculation tool developed to make detailed analyzes systematically and accurately. The most important advantage of this study is the development of an economic analysis model and algorithmic structure for basic reduction methods according to field data. It is thought that the cost analysis and algorithmic structures developed will make a significant contribution to the economic leakage level analysis and serve as a reference for sustainable water loss management.

China's global value chain linkage and logistics performances in emerging ASEAN economies

AbstractThis paper aims to evaluate the extent of China's forward linkage of global value chains (GVCs) with emerging market economies of the Association of Southeast Asian Nations (ASEAN) compared to those with the United States and Japan, and also to examine the nexus of China's forward GVC linkage with logistics performances in emerging ASEAN economies as China's trade partners. This study uses the UNCTAD‐Eora Database and applies a structural gravity trade model for empirical analysis. The statistical observations identified the major position of China's GVC, which has transformed from a backward linkage to a forward linkage since the mid‐2000s. The empirical estimation verified that there is less linkage in China's forward GVC with emerging ASEAN economies than with the United States and Japan, and demonstrated that the lack of logistics performances in emerging ASEAN economies has been a significant factor in explaining the less linkage in China's forward GVC with them.

A study of CO2 emissions in China's domestic construction industry based on non-competitive input-output

To accurately calculate the actual CO 2 emissions of China's domestic construction industry (CDC) under the influence of international trade factors, an improved import proportion method (IIPM) was suggested in this paper based on the non-competitive input-output (NC-IO) table in 2017. The NC-IO table of 10 years from 2010 to 2019 was complemented in combination with the Row arrange series (RAS) method, and the CO 2 emissions of the CDC in the 10 years were calculated by the input-output (I-O) method. The results reveal that CO 2 emissions of the CDC keep increasing, with an annual increase of 6.57%, and the proportion thereof to domestic CO 2 emissions has increased from 17.00% to 22.52%, although the carbon intensity has decreased by 39.6%. On this basis, by Structural decomposition analysis (SDA) model analysis, the change in CO 2 emission influencing factors in the past 10 years was analyzed from the perspective of CO 2 emissions factor, industrial structure, and domestic final demand. The results indicate that the IIPM is more accurate and the calculation is more reliable based on 5 indicators. Additionally, the optimization of the industrial structure after 2015 has had a significant dampening effect, and the final demand has played an absolute leading role in improving CO 2 emissions. From the perspective of final demand, the current emission reduction measures in the CDC, including prefabricated buildings, are not satisfactorily effective, and more efforts need to be made in emission reduction. Furthermore, the contradiction between the growth of final demand and the demand for CO 2 emissions reduction is prominent.

Transfer Characteristics of Embodied Carbon Emissions in Export Trade—Evidence from China

The export trade of China, the factory of the world, promotes economic growth while increasing carbon emissions. This study integrates China’s multi-regional input–output table and the world input–output table to explore the international transfer-in effect and foreign spillover effect of carbon emissions caused by China’s export trade. A structural decomposition analysis model is also used to identify the influencing factors of carbon emissions caused by China’s export trade of intermediate and final products. Results show that: (1) 45.13–58.87% of the transfer-in carbon emissions resulting from China’s export trade are caused by developed countries and 41.13–54.87% by developing countries; (2) the foreign spillover effect caused by China’s export trade is primarily associated with developing countries, accounting for 63.79–69.61%; (3) carbon emissions caused by the export of intermediate products (final products) in China are primarily caused by the scale effect (industrial linkage). China should adjust the structure of its export trade in accordance with the characteristics of embodied carbon emissions in export trade to achieve low-carbon development.

Analysis of Industrial Carbon Transfer in Beijing-Tianjin-Hebei City Cluster and Surrounding Areas

To achieve the goal of carbon neutrality and win the blue-sky defense battle, the environmental situation in Beijing-Tianjin-Hebei and surrounding areas is still grim, and the optimization of its industrial structure and energy structure is imminent. With the rapid development of interregional trade in intermediate products, carbon emissions are transferred across regions with the trade. Due to the large differences in the technology, industrial structure, and economic development of cities, extending the environmental governance chain of Beijing-Tianjin-Hebei and surrounding areas is indispensable. In this article, based on the interregional input-output tables in 2002, 2007, and 2012, we establish the average propagation length (APL) model and the structural path analysis model Structural Path Analysis model for analyzing the carbon conduction relationship in Beijing-Tianjin-Hebei. And we also compare the situation of the Yangtze River Delta and the Pearl River Delta. The results show that: i) From perspective of the whole urban clusters, Beijing-Tianjin-Hebei has obvious characteristics of coal-fired urban clusters. More than 65% of the carbon-containing resources in Hebei’s coal industry are transferred to the electricity and heat industry. In the carbon conduction chain, the carbon emissions caused by electricity and heat industry, which acts as an intermediary, account for more than 85% of the total emissions. ii) From the perspective of industrial structure transfer within the urban clusters, Hebei Province has an important resource support position. Its secondary industry can not only effectively alleviate the shortage of energy supply in other resource provinces, but also has great development potential in the improvement of economic benefits. iii) From the perspective of specific industry sectors, resource provinces such as Shanxi and Inner Mongolia have high carbon emission coefficients in the electricity and heat industry, which is the main reason for the high carbon emissions in the transfer chain.

MODELING OF THE BEHAVIOR OF REINFORCED CONCRETE ELEMENTS, STRENGTHENED IN THE TENSIONED ZONE, UNDER THE ACTION OF A LONG-TERM LOAD

This article provides suggestions for improving the method for analysis of the parameters of the stress-strain state of bent reinforced concrete elements, strengthened in the tension zone, taking into account the effects of concrete creep under a long-term load. The general non-linear deformation model for structural analysis of reinforced concrete elements under the combined action of bending moments and longitudinal forces is taken as a basis, using a mathematical description of the deformation diagrams of concrete and reinforcement. The proposed model makes it possible to take into account the effects of changes in deformations in concrete under the action of a long-term load. Experimental verification showed a satisfactory convergence of the results of the analysis by the proposed method with the experimental data.