Search Results (37)

Indonesia’s commitment to digital transformation is exemplified by the Gerakan 100 Smart City program, aiming to enhance public sector performance through technology integration. This study examines how information technology capability and 21st century digital skills influence public sector performance, mediated by managerial digital readiness and moderated by digital leadership. Grounded in Dynamic Capability Theory and Upper Echelon Theory, data from 1380 civil servants were analyzed using PLS-SEM via SmartPLS 4.1.0.9. Results show that both IT capability and digital skills significantly improve managerial digital readiness, which in turn positively impacts public sector performance. Managerial readiness mediates the effect of both predictors on performance, while digital leadership strengthens these relationships. Theoretically, this study frames managerial digital readiness as a dynamic capability shaped by leadership cognition. Practically, it highlights the importance of aligning infrastructure, skills, and leadership development to advance digital governance. Future research should consider longitudinal, multilevel, and qualitative designs to deepen insights. Full article

The manufacturing industry serves as critical carrier for the empowerment of digital technologies and is the cornerstone of digital innovation and development. Smart transformation (ST), propelled by technological advancements, has become a prominent area of academic research, but its role in fostering the co-development of manufacturing industries has been overlooked. This study employs an empirical approach to examine the causal mechanisms linking ST with regional economic development (RED), particularly emphasizing the mediating effects exerted by regional innovation capacity (RIC). Leveraging panel data from 29 Chinese provinces spanning the period from 2009 to 2023, we constructed an econometric model for analysis. The findings reveal that ST has a direct effect on RED, knowledge innovation capacity (KIC), and innovation infrastructure (II) partially mediated, while technology innovation capacity (TIC) completely mediated the relationship. Theoretical contributions manifest in three dimensions: First, drawing on the sociotechnical system theory and technology diffusion theory, this paper establishes a multidimensional framework of ST, deepening the theoretical underpinnings of smart technology application in the manufacturing industry from three aspects: smart base input, smart applications, and smart market benefits. Second, it extends regional innovation theory and endogenous growth theory by conceptualizing RIC in three sub-capabilities (KIC, TIC, and II). Third, it contributes to the RED literature by exploring the coupling effect between manufacturing industry clusters and the development of RIC and ultimately concludes with targeted policy recommendations for optimizing ST strategies to foster RED in different manufacturing industries. Full article

With the use of digital technologies in today’s innovation era, the financial sector has transformed how they facilitate customer business and generate a high level of revenue. This study aims to explore the relationship between innovative work behavior (IWB), digital transformation (DT), and organizational financial performance (OFP) to analyze the mediating role of workers’ psychological empowerment (PE) between independent and dependent variables. Further, we examined the moderating role of smart technologies (ST) between PE and OFP. This study collected data from Saudi banking sector employees using a well-structured questionnaire adopted from previous literature. Next, Smart-PLS was used to analyze the data using the structural equation modeling-partial least squares (SEM-PLS) approach. The results reveal that IW positively relates to OFP, with PE mediating this relationship. Furthermore, DT positively affects OFP. ST acts as a positive moderator that enhances workers’ PE and OFP. Meanwhile, PE, as a mediator, positively relates DT and IWB to OFP. Overall, this study makes valuable theoretical, empirical, and practical contributions, which can benefit bank management, policymakers, and future academic research. Full article

The gradual replacement of conventional generators with variable renewable energy sources (RES) will reduce their online frequency regulation (FR) resources and degrade their overall frequency control capabilities. Although various inertia emulation methods exist, shaping load consumption is considered a more effective strategy during emergency conditions than under-frequency load shedding. Managing loads following frequency excursions can support grid stability owing to rapid power response. In this context, a Smart Transformer (ST)-based FR framework for a RES-penetrated power system is studied in this paper. The ST, with its distinctive features, effectively shapes the load profile through online load sensitivity identification-based control, aiding in the stabilization of grid frequency. This paper also proposes a tilt integral second-order double derivative (TIDD²) controller for a secondary loop whose parameters are optimized using the Learner Performance-based Behavior (LPB) algorithm. A thorough investigation reveals that the response from ST controlling the voltage-dependent load in the presence of TIDD² controllers can greatly enhance system performance by damping oscillations and peak deviations. In addition, the performance of Proportional–Integral–Derivative and TIDD² considering ST in the primary loop is compared to delineate the robustness of the LPB-based TIDD² controller. It is found that the proposed control scheme offers greater controllability and flexibility, enhancing the system’s dynamic performance. Full article

Quality improvement is essential for a nation’s economy to transition from large to strong. In the 21st century, a new wave of quality development has emerged globally, and upgrading the quality of enterprise export products is a key measure for driving exports and supporting high-quality economic development. The development of artificial intelligence, as the new core engine driving technological revolution and industrial transformation, will profoundly alter various aspects of economic activities, including production, distribution, exchange, and consumption. Exploring and cultivating new artificial intelligence-driven momentum to enhance the quality of enterprise export products is inevitably a major theoretical and practical issue of common interest to governments, enterprises, and academia. This paper uses China, a major developing and export-oriented economy, as a case study to explore the policy measures for stimulating new momentum in artificial intelligence development and their effects and transmission mechanisms on improving the quality of enterprise export products. Specifically, it constructs a theoretical model to examine the relationship between smart city construction, artificial intelligence development, and the quality of enterprise export products. By considering the smart city construction projects launched by the Chinese government as a quasi-natural experiment to facilitate artificial intelligence development, the study employs matched city-enterprise data from 2007 to 2015 and utilizes a difference-in-differences (DID) methodology to empirically test the impact of smart city construction on enhancing the quality of enterprise export products. According to the study, the policy-driven nature of smart city construction significantly enhances the quality of enterprise export products. This beneficial impact is particularly evident in the eastern regions, as well as in labor-intensive and capital-intensive industries, and among foreign-invested and private enterprises. Mechanism tests and additional analyses indicate that artificial intelligence development is significantly more advanced in smart cities than in non-smart cities, with the gap between them steadily widening. The construction of smart cities significantly advances artificial intelligence development, which subsequently enhances the quality of enterprise export products. Furthermore, smart cities can substantially contribute to this improvement by facilitating a more efficient, market-oriented allocation of resources. Full article

Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHMs) present a promising solution to enhance the efficiency of conventional microgrids (MGs) and facilitate higher integration of Distributed Energy Resources (DERs), simultaneously managing active and reactive power dispatch. However, MHMs face challenges in resource management under uncertainty and control of electronic converters linked to the ST and DERs, complicating the pursuit of optimal system performance. This paper introduces a Data-Driven Distributionally Robust Optimization (DDDRO) approach for day-ahead operation planning in ST-based MHMs, focusing on minimizing network losses, voltage deviations, and operational costs by optimizing the reactive power dispatch of DERs. The approach accounts for uncertainties in photovoltaic generator (PVG) output and demand. The Column-and-Constraint Generation (C&CG) algorithm and the Duality-Free Decomposition (DFD) method are employed. The initial mixed-integer non-linear planning problem is also reformulated into a mixed-integer (MI) Second-Order Cone Programming (SOCP) problem using second-order cone relaxation and a positive octagonal constraint method. Simulation results on a connected MHM system validate the model’s efficacy and performance. The study also highlights the advantages of the meshed MG structure and the positive impact of integrating the ST into MHMs, leveraging the multi-stage converter’s flexibility for optimal energy management under uncertain conditions. Full article

This research addresses the urgent challenges posed by rapid urbanization and climate change through an integrated interdisciplinary approach combining advanced technologies with rigorous scientific exploration. The comprehensive analysis focused on Wuhan, China, spanning decades of meteorological and land-use data to trace extreme urbanization trajectories and reveal intricate temporal and spatial patterns. Employing the innovative 360° radial Fibonacci geometric growth framework, the study facilitated a meticulous dissection of urban morphology at granular scales, establishing a model that combined fixed and mobile observational techniques to uncover climatic shifts and spatial transformations. Geographic information systems and computational fluid dynamics were pivotal tools used to explore the intricate interplay between urban structures and their environments. These analyses elucidated the nuanced impact of diverse morphosectors on local conditions. Furthermore, genetic algorithms were harnessed to distill meaningful relationships from the extensive data collected, optimizing spatial arrangements to enhance urban resilience and sustainability. This pioneering interdisciplinary approach not only illuminates the complex dynamics of urban ecosystems but also offers transformative insights for designing smarter, more adaptable cities. The findings underscore the critical role of green spaces in mitigating urban heat island effects. This highlights the imperative for sustainable urban planning to address the multifaceted challenges of the 21st century, promoting long-term environmental sustainability and urban health, particularly in the context of tomorrow’s climate-adaptive smart cities. Full article

Heusler alloys, which were unintentionally discovered at the start of the 20th century, have become intriguing materials for many extraordinary functional applications in the 21st century, including smart devices, spintronics, magnetic refrigeration and the shape memory effect. With this review article, we would like to provide a comprehensive review on the recent progress in the development of Heusler alloys, especially Ni-Mn based ones, focusing on their structural crystallinity, order-disorder atoms, phase changes and magnetic ordering atoms. The characterization of the different structures of these types of materials is needed, where a detailed exploration of the crystal structure is presented, encompassing the influence of temperature and compositional variations on the exhibited phases. Hence, this class of materials, present at high temperatures, consist of an ordered austenite with a face-centered cubic (FCC) superlattice as an L2₁ structure, or body-centered cubic (BCC) unit cell as a B2 structure. However, a low-temperature martensite structure can be produced as an L10, 10M or 14M martensite structures. The crystal lattice structure is highly dependent on the specific elements comprising the alloy. Additionally, special emphasis is placed on phase transitions within Heusler alloys, including martensitic transformations ranging above, near or below room temperature and magnetic transitions. Therefore, divers’ crystallographic defects can be presented in such types of materials affecting their structural and magnetic properties. Moreover, an important property of Heusler compounds, which is the ability to regulate the valence electron concentration through element substitution, is discussed. The possible challenges and remaining issues are briefly discussed. Full article

The smart transformer (ST) is a multiport and multi-stage converter that allows for the formation of meshed hybrid microgrids (MHMs) by enabling AC-DC ports in medium and low voltage. This type of microgrid has advantages over the performance of conventional hybrid AC-DC microgrids (HMGs); however, the number of degrees of freedom of the ST increases the complexity of the energy management systems (EMSs), which require adequate and accurate modeling of the power flow of the converters and the MG to find the feasible solution of optimal power flow (OPF) problems in the MHM. An ST’s equivalent power flow model is proposed for formulating the MHM OPF problem and developing low-frequency equivalent models integrated with a decoupled hierarchical control architecture under a real-time simulation approach to the ST-based MHM. A simulation model of the MHM in the Simulink^® environment of Matlab^{® 9.12} is developed and implemented under a digital real-time simulation (DRTS) approach on the OPAL-RT^® platform. This model allows for determining the accuracy of the developed equivalent models, both low-frequency and power flow, and determining the MHM performance based on optimal day-ahead scheduling. Simulation test results demonstrated the ST equivalent model’s accuracy and the MHM’s accuracy for OPF problems with an optimal day-ahead scheduling horizon based on the model-in-the-loop (MIL) and DRTS approach. Full article

The concepts of healthy cities and smart cities are popular in emerging research in the 21st century. This study focuses on the existing interrelations between the two notions in terms of socio-spatial quality, technology, and innovation, particularly regarding industrial sites that no longer have a role and constitute ‘urban voids’ with high volumetric concentrations. The fast expansion of cities and the de-industrialization phenomena have resulted in such void-producing blights that compromise public health; environmental quality; and social, economic, and living conditions. Therefore, the authors intend to emphasize the relevance of citizens’ and communities’ engagement in shaping new healthy and smart urban environments. The present method relies on a literature review to describe the current theoretical and practical dimensions of such topics, identifying synergies and trade-offs. After this, a case study in China is presented to support the discussion. The site, a former granary, is located in Lianshi, a traditional water-edge town in the central area of the Yangtze River Delta. The proposed example enhances solutions that meet healthy and smart requirements, transforming the former industrial area into a social catalyst, acting as an effective motivator for urban development. One such theoretical approach is exemplified by a project that won a national architecture competition in 2018, the ‘Taihu Cultural Heritage Rehabilitation Competition’. The latter is then validated through practical solutions in a real-world context by analyzing the ‘Cuckoo’ project developed in 2021 for the same area. Overall, the integration of healthy and smart elements is proposed by the authors as an effective method to achieve more holistic and sustainable city development from both theoretical and practical points of view. Full article

This article shows the potential of smart city development in revitalizing urban industrial heritage and traditional industrial blocks. It highlights the challenges faced by these areas, such as aging infrastructure, pollution, and neglect. Smart city technologies are examined as effective solutions for addressing these challenges by promoting efficient resource utilization, improving mobility and connectivity, and enhancing the quality of the built environment. International examples of smart city initiatives implemented in industrial heritage sites and traditional industrial blocks are presented to demonstrate the potential benefits of these technologies. This article emphasizes the importance of inclusivity, sustainability, and community engagement in the revitalization process. It argues that smart city development should prioritize the needs and aspirations of local communities, leveraging their knowledge and expertise for long-term success and sustainability. This article underscores the significance of adopting a comprehensive and integrated approach to urban revitalization that considers social, economic, and environmental dimensions of sustainability. It suggests that smart city development can act as a catalyst for transforming urban industrial areas into thriving and resilient landscapes capable of addressing the challenges of the 21st century. This article aims to explore the potential of smart city development in revitalizing urban industrial heritage and traditional industrial blocks while advocating for equitable outcomes and sustainable urban environments. Full article

With the advent of smart mobile devices, end users get used to transmitting and storing their individual privacy in them, which, however, has aroused prominent security concerns inevitably. In recent years, numerous researchers have primarily proposed to utilize motion sensors to explore implicit authentication techniques. Nonetheless, for them, there are some significant challenges in real-world scenarios. For example, depending on the expert knowledge, the authentication accuracy is relatively low due to some difficulties in extracting user micro features, and noisy labels in the training phrase. To this end, this paper presents a real-time sensor-based mobile user authentication approach, ST-SVD, a semi-supervised Teacher–Student (TS) tri-training algorithm, and a system with client–server (C-S) architecture. (1) With S-transform and singular value decomposition (ST-SVD), we enhance user micro features by transforming time-series signals into 2D time-frequency images. (2) We employ a Teacher–Student Tri-Training algorithm to reduce label noise within the training sets. (3) To obtain a set of robust parameters for user authentication, we input the well-labeled samples into a CNN (convolutional neural network) model, which validates our proposed system. Experimental results on large-scale datasets show that our approach achieves authentication accuracy of 96.32%, higher than the existing state-of-the-art methods. Full article

Decision support tools are needed to ensure that appropriately timed and place-based adaptation is deployed in natural resource policy, planning, and management. Driven by accelerating climate change, analytical frameworks for adaptation are emerging to assist with these decisions. There is a natural relationship between climate change vulnerability assessments and adaptation responses, where low to high relative climate change vulnerability suggests “resistance” to “transformation” strategies for adaptation. The NatureServe Habitat Climate Change Vulnerability Index (HCCVI) embodies a process for ecosystem assessment that integrates both climate and non-climate data and knowledge to document the relative vulnerability of a given habitat or ecosystem type. The framework addresses climate exposure and ecosystem resilience. Since most measures of exposure and resilience are mapped, they can be utilized to create map zones that suggest climate-smart adaptation. We applied the HCCVI to a cross-section of 10 pinyon pine and juniper woodland ecosystem types in western North America. We then demonstrate the application of these outputs to adaptation zonation. Climate exposure defines relative adaptation strategies, while measures of resilience suggest specific priorities for habitat restoration and maintenance. By the mid-21st century, 3% and 23% of the combined area of these types in the United States was categorized as Directed Transformation or Autonomous Transformation, respectively. In just 10% of the combined areas for these types, Passive Resistance strategies are suggested. Full article

Smart cities are rapidly evolving concept-transforming urban developments in the 21st century. Smart cities use advanced technologies and data analytics to improve the quality of life for their citizens, increase the efficiency of infrastructure and services, and promote sustainable economic growth. Smart cities integrate multiple domains, including transportation, energy, health, education, and governance, to create an interconnected and intelligent urban environment. Our research study methodology was a structured literature review using Web of Science and Google Scholar and ten smart city research questions. The research questions included smart city definitions, advantages, disadvantages, implementation challenges, funding, types of applications, quantitative techniques for analysis, and prioritization metrics. In addition, our study analyzes the implementation of smart city solutions in international contexts and proposes strategies to overcome implementation challenges. The integration of technology and data-driven solutions in smart cities has the potential to revolutionize urban living by providing citizens with personalized and accessible services. However, the implementation also presents challenges, including data privacy concerns, unequal access to technology, and the need for collaboration across private, public, and government sectors. This study provides insights into the current state and future prospects of smart cities and presents an analysis of the challenges and opportunities they present. In addition, we propose a concise definition for smart cities: “Smart cities use digital technologies, communication technologies, and data analytics to create an efficient and effective service environment that improves urban quality of life and promotes sustainability”. Smart cities represent a promising avenue for urban development. As cities continue to grow and face increasingly complex challenges, the integration of advanced technologies and data-driven solutions can help to create more sustainable communities. Full article

The sustainable provision of mankind with energy and mineral raw materials is associated with an increase not only in industrial but also in the ecological and economic development of the raw material sector. Expanding demand for energy, metals, building and chemical raw materials on the one hand, and the deterioration of the living environment along with a growth of raw materials extraction on the other, put the human-centric development of mining at the forefront. This forms a transition trend from Mining 4.0 technologies such as artificial intelligence, big data, smart sensors and robots, machine vision, etc., to Mining 5.0, presented with collaborative robots and deserted enterprises, bioextraction of useful minerals, postmining, and revitalization of mining areas. This “bridge” is formed by the technological convergence of information, cognitive, and biochemical technologies with traditional geotechnology, which should radically change the role of the resource sector in the economy and society of the 21st century. The transition from Mining 3.0 to 4.0 cannot be considered complete. However, at the same time, the foundation is already being laid for the transition to Mining 5.0, inspired, on the one hand, by an unprecedented gain in productivity, labor safety, and predictability of commodity markets, on the other hand, by the upcoming onset of Industry 5.0. This review provides a multilateral observation of the conditions, processes, and features of the current transition to Mining 4.0 and the upcoming transformation on the Mining 5.0 platform, highlighting its core and prospects for replacing humans with collaborated robots and artificial intelligence. In addition, the main limitations of the transition to Mining 5.0 are discussed, the overcoming of which is associated with the development of green mining and ESG (environment, social, and governance) investment. Full article