Data Computation Research Articles

A paradigm shift in education: Prospects and recommendations for schools in 2030

The interest of this study is borne out of an attempt to investigate the drastic change that technology has brought to the instructional core. The future of schools is exponentially upgrading through the integration of sophisticated educational systems that appear to create a whole new trajectory for all education stakeholders. Instruction will be adaptive and assessment will be real-time. In this profound and complex scenario, current schools will no longer be the epicenters of knowledge as AI-powered educational tools will hegemonize and remarkably offer extraordinarily enticing adaptive learning opportunities through smart classrooms and other technological trends and patterns, such as Cloud Computing (connectivity and data security) and the Internet of Things (IoT) (intelligent whiteboards). Needless to say, technology enhanced learning will unequivocally become the pinnacle of education. Therefore, many educators will have to expand their instructional technology to rise to the occasion.

Energy-focused simulation of edge computing architectures in 5G networks

While cloud computing is crucial in processing data from devices with low computational power, the latency introduced by the Internet backhaul limits real-time applications. By situating computing resources at the network’s edge, edge computing offers low-latency services by offloading computations from high-performance computing (HPC) data centers to the edge servers, reducing wide Area network (WAN) strain. As a result, edge computing has unlocked opportunities for innovative applications that were previously unfeasible, such as connected vehicles or medical robotics. Nonetheless, deploying the infrastructure required to support edge computing services raises sustainability and energy consumption concerns. Consequently, the development of tools enabling researchers to explore innovative approaches to reducing the energy impact of edge computing is crucial. In this work, we present MintEDGE, a network simulator focused on the energy consumption of edge computing. Our simulator allows testing energy-saving approaches and task placement algorithms in realistic large-scale scenarios encompassing entire regions.

DNA as a universal chemical substrate for computing and data storage.

DNA computing and DNA data storage are emerging fields that are unlocking new possibilities in information technology and diagnostics. These approaches use DNA molecules as a computing substrate or a storage medium, offering nanoscale compactness and operation in unconventional media (including aqueous solutions, water-in-oil microemulsions and self-assembled membranized compartments) for applications beyond traditional silicon-based computing systems. To build a functional DNA computer that can process and store molecular information necessitates the continued development of strategies for computing and data storage, as well as bridging the gap between these fields. In this Review, we explore how DNA can be leveraged in the context of DNA computing with a focus on neural networks and compartmentalized DNA circuits. We also discuss emerging approaches to the storage of data in DNA and associated topics such as the writing, reading, retrieval and post-synthesis editing of DNA-encoded data. Finally, we provide insights into how DNA computing can be integrated with DNA data storage and explore the use of DNA for near-memory computing for future information technology and health analysis applications.

Research on industrial risk early warning algorithms based on edge computing and multimodal data

AbstractTo achieve real‐time and effective prediction of industrial site risks, this paper proposes an industrial risk prediction framework for multimodal data based on edge computing. First, the authors gather and annotate industrial risk multimodal data that consist of text descriptions, images, and videos. Then, the authors transfer the data to the edge server, and apply deep learning models such as Bidirectional Encoder Representations from Transformers (BERT), ResNet etc., to extract features and learn representations for text, image, and video data respectively. The authors input the fused feature data into an enhanced long short term memory (LSTM) model and train it on the dataset. Finally, the authors perform the risk prediction based on the collected multimodal data. The experimental results demonstrate that the method proposed in this paper exhibits superior performance, achieving a 1.4% enhancement in predictive accuracy.

The evolution of smart hotels: A bibliometric review of the past, present and future trends

This study provides a bibliometric analysis of smart hotel research, drawing from 613 publications in the Web of Science (WoS) database to examine scholarly trends and developments in this dynamic field. Smart hotels, characterized by integrating advanced technologies such as AI, IoT, cloud computing, and big data, aim to redefine customer experiences and operational efficiency. Utilizing co-citation and co-word analysis techniques, the research delves into the depth of literature from past to future trends. In co-citation analysis, clusters including "Sustainable Hotel and Green Hotel", "Theories Integration in Smart Hotel Research", and "Consumers' Decisions about Green Hotels" underscore the pivotal areas of past and current research. Co-word analysis further reveals emergent trend clusters: "The New Era of Sustainable Tourism", "Elevating Standards and Guest Loyalty", and "Hotels' New Sustainable Blueprint in Modern Travel". These clusters reflect the industry's evolving focus on sustainability and technology-enhanced guest experiences. Theoretically, this research bridges gaps in smart hotel literature, proposing new frameworks for understanding customer decisions amid technological advancements and environmental responsibilities. Practically, it offers valuable insights for hotel managers, guiding technology integration strategies for enhanced efficiency and customer loyalty while underscoring the critical role of green strategies and sustainability.

Navigating Digital Transformation and Knowledge Structures: Insights for Small and Medium-Sized Enterprises

AbstractIn today’s rapidly evolving business landscape, digital transformation has become synonymous with the strategic integration of cloud computing, mobile internet, social media, and big data. This paradigm shift has reshaped traditional business models, presenting organizational challenges and opportunities. Small and medium-sized enterprises (SMEs), in particular, face a unique set of obstacles as they navigate the complexities of this digital revolution. This research paper delves into the intricacies of digital transformation within the SME context. It acknowledges the significance of this transformation for enhancing core competencies and sustainable development, emphasizing the convergence of business strategy and technological advancement. To provide a comprehensive understanding, this study employs bibliometric analysis using CiteSpace, shedding light on underappreciated procedures, steps, and data related to SMEs’ digital transformation. A systematic literature review extracts a theoretical framework, offering valuable insights and guidance for SMEs operating in an increasingly digitalized business environment. The research contributes to the ongoing global discussion on digital transformation and highlights differences and similarities across various research domains. It identifies thematic clusters such as “Digital transformation of SMEs,” “Industry 4.0,” “Adoption paths,” and “Business model,” revealing trends, themes, and shifts in studying digital transformation in SMEs worldwide. This paper provides a valuable synthesis of previous research accomplishments, offering theoretical implications for academia and practical managerial insights. It emphasizes the importance of collaborative mechanisms and research networks, fostering knowledge exchange and driving innovation in the field of digital transformation for SMEs, both nationally and internationally.

Retracted: Optimization of the Marketing Management System Based on Cloud Computing and Big Data

Retracted: Optimization of the Marketing Management System Based on Cloud Computing and Big Data

Is Digital Transformation a Burden or a Help? From the Perspective of Enterprise Sustainable Development

Sustainability has become increasingly critical to the development of modern companies. As it emphasizes the generation of value across three dimensions—economics, the environment, and society—sustainable development underscores its significance. Based on the value that a company delivers at a particular stage of the sustainable development process, this study proposes revenue as a measure to quantify stakeholder interest. Utilizing a fixed effects model with 2211 listed companies in 11 years, this study explores how organizations’ economic, environmental, and social inputs influence the creation of sustainability value on these three pillars, alongside the impact of four major digital technologies (artificial intelligence, blockchain, cloud computing, and big data). The study reveals that companies’ contributions in these dimensions significantly enhance the output of values. Each of the four digital technologies exerts a distinct moderating influence. We provide a thorough look at the “input-output” relationship of sustainable value creation. Our research highlights the varying effects on sustainable development of companies’ contributions to the economy, the environment, and society, as well as companies’ adoption of digital technologies.

ТРАНСФОРМАЦІЯ СТРУКТУРИ СИСТЕМИ ВАЛЮТНОГО КОНТРОЛЮ В ЦИФРОВІЙ ЕКОНОМІЦІ АЗЕРБАЙДЖАНУ

Digital transformation in the banking and financial services sector largely involves a shift towards online and digital services from top-down branch banking, integrating digital systems, customer service platforms, applications and infrastructure. The purpose of the article is characterise the transformation of the structure of the currency control system in the digital economy of Azerbaijan. The subject of the study is processes of transformation of the currency control system structure in the digital economy of Azerbaijan. The methodological basis and information base of the research are current scientific and applied research, statistical information. The article uses a number of methods, including analysis, synthesis, comparison and generalization. The main hypothesis of the study was the assumption that the efficiency of economic management and the financial condition of the public sector depend on the quality of budget forecasting and planning, because they are the key to the sustainable development of socio-economic processes. Presenting main material. Technologies being implemented include blockchain, artificial intelligence (AI), cloud computing, machine learning, and customer data collection, management and analysis. With increasing adoption of FinTech (innovative technology supporting banking and financial services) disrupting the sector, it is attracting regulatory interest and prompting stricter regulatory standards.The originality and practical significance of the research.Systemic reforms of the payment ecosystem not only affect the development of financial markets and the country’s economy as a whole, but also ensure safe and efficient payments between business entities. Conclusions. Deepening digital transformation in the banking system and expanding the use of innovative payment solutions makes electronic payments an integral part of our daily lives and at the same time increases the competitiveness of the banking system as a whole

The Impact of Fintech Innovation on Bank’s Performance: Evidence from the Kingdom of Bahrain

This study investigates the impact of bank-level Financial Technology (Fintech) innovations on banks’ performance in the Kingdom of Bahrain from 2012-2021. Annual data of banks listed in Bahrain’s Bourse has been utilized to achieve this objective. In addition, bank-level FinTech indices have been constructed by a textual analysis method that assesses input dimensions through 32 keywords under four categories, including artificial intelligence, blockchain, cloud computing, and big data; FinTech output dimension is evaluated through payment and settlement, resource allocation, risk management, and channel construction technology. Using different panel data estimators, such as pooled OLS, fixed effects, random effects, and panel-corrected standard errors linear regression, results show that FinTech innovations increase banks’ performance. In addition, the findings demonstrate that banks' capital adequacy ratio, earnings ability, total assets, and annual GDP growth rate also significantly positively impact bank performance. Years in business have a significant adverse effect on bank performance. Interestingly, conventional and state-owned banks have a higher positive impact on returns on assets (ROA) than Islamic and privately owned banks. Policymakers and investors should pay close attention to facilitating ongoing FinTech innovations in the Kingdom of Bahrain to create opportunities and build a more inclusive and efficient financial sector.

Digital transformation in food supply chains: an implementation framework

PurposeDigital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).Design/methodology/approachA systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.FindingsThe combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.Originality/valueThe study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.

Logic Gate Circuits Based on CeOx/WOy Memristor for the Odd/Even Checker and Encryption/Decryption of Image Applications

AbstractDue to its powerful brain‐like parallel computing and efficient data processing capabilities, memristors are considered to be the core components for building the next generation of artificial intelligence systems. In this study, the CeOx/WOy heterojunction is employed as the functional layer, and various metal materials are utilized as the top electrode to fabricate the memristor. The results indicate that the memristive performance of the Ag/CeOx/WOy/ITO device can be improved by using Ag as the top electrode. By studying the conductivity mechanism of the device, a conductivity model is established that regulates oxygen vacancies and Ag conductive filaments. Furthermore, using the as‐prepared memristor, it is constructed four basic digital logic circuits: OR, AND, XOR, and XNOR, as well as a half adder and a full adder that can be used for digital arithmetic operations. Specifically, an odd/even checker is developed based on XOR and XNOR logic circuits to verify the correctness of data transmission. Finally, it is also designed and implemented a cryptographic array based on a memristor, which can be applied to encrypt and decrypt a series of numbers and images. Therefore, this work extends the application of memristor toward digital circuits, information transmission, data processing and image security encryption.

Novel enterprises digital transformation influence empirical study.

With the rapid development of technologies such as cloud computing and big data, various levels of government departments in the country have successively introduced digital subsidy policies to promote enterprises' digital transformation. However, the effectiveness of these policies and their ability to truly achieve policy objectives have become pressing concerns across society. Against this backdrop, this paper employs a moderated mediation effects model to empirically analyze the incentive effects of financial subsidies on the digital transformation of A-share listed manufacturing companies in the Shanghai and Shenzhen stock markets from 2013 to 2022. The research findings indicate a significant promotion effect of financial subsidies on the digital transformation of manufacturing enterprises, especially demonstrating a notable incentive impact on the digital transformation of large enterprises, non-asset-intensive enterprises, technology-intensive enterprises, and non-labor-intensive enterprises. However, the incentive effect on the digital transformation of small and medium-sized enterprises (SMEs), asset-intensive enterprises, non-technology-intensive enterprises, and labor-intensive enterprises is not significant. Notably, the expansion of financial subsidies positively influences the augmentation of R&D investment within manufacturing enterprises, subsequently providing indirect encouragement for their digital transformation. Additionally, the incorporation of the degree of marketization implies its potential to moderate both the direct and indirect impacts of financial subsidies on enterprise digital transformation. This study enriches the research on the mechanism of the role of financial subsidies in digital transformation and provides empirical evidence on how market participation influences the effects of financial subsidies, thereby assisting policymakers in comprehensively understanding the impact of financial subsidy policies on different types of enterprises.

Forest Disturbance Monitoring Using Cloud-Based Sentinel-2 Satellite Imagery and Machine Learning.

Forest damage has become more frequent in Hungary in the last decades, and remote sensing offers a powerful tool for monitoring them rapidly and cost-effectively. A combined approach was developed to utilise high-resolution ESA Sentinel-2 satellite imagery and Google Earth Engine cloud computing and field-based forest inventory data. Maps and charts were derived from vegetation indices (NDVI and Z∙NDVI) of satellite images to detect forest disturbances in the Hungarian study site for the period of 2017-2020. The NDVI maps were classified to reveal forest disturbances, and the cloud-based method successfully showed drought and frost damage in the oak-dominated Nagyerdő forest of Debrecen. Differences in the reactions to damage between tree species were visible on the index maps; therefore, a random forest machine learning classifier was applied to show the spatial distribution of dominant species. An accuracy assessment was accomplished with confusion matrices that compared classified index maps to field-surveyed data, demonstrating 99.1% producer, 71% user, and 71% total accuracies for forest damage and 81.9% for tree species. Based on the results of this study and the resilience of Google Earth Engine, the presented method has the potential to be extended to monitor all of Hungary in a faster, more accurate way using systematically collected field-data, the latest satellite imagery, and artificial intelligence.

Upaya Surat Kabar Harian Umum Haluan Padang Dalam Mempertahakan Eksistensi Di Era Media Online

The rapid development of information and communication technology has caused a shift in information consumption patterns in society which has resulted in competition in the media industry, one of which is print media, where currently print media not only competes with other print media, but also competes with online media which is much interactive and interactive. efficient. Many newspapers have gone out of business because they failed to maintain their existence amidst the rapid growth of online media. This research aims to determine the efforts made by the Haluan Padang General Daily Newspaper in maintaining its existence in the online media era as one of the oldest conventional media in West Sumatra. This research is descriptive qualitative research which produces descriptive data in the form of writing or speech, as well as the behavior of people being observed. This method is applied to describe and analyze phenomena, events, social activities, attitudes, beliefs, perceptions, thoughts of people individually and in groups. To describe this research using the media convergence theory put forward by Henry Jenkins (2006) in his book entitled "Convergence Culture: Where Old and New Media Collide" there are 3 elements of convergence, namely Computing (data on computers), Communication (communication), and Content ( content material) and Adaptation Me theory. The Haluan Padang General Daily Newspaper has made efforts to maintain its existence by carrying out computer/technology convergence, business convergence, content convergence as well as promotional or personal branding efforts. Through these efforts, Haluan Padang Daily remains relevant and competitive in an increasingly competitive media market. Despite facing various challenges, dedication to providing quality information and strong involvement with the community is the key for print media such as Harian Haluan Padang to continue to survive and face challenges in the future or what is known as the Cultivation Adaptation Theory by George Gerbner in the 1960s as supporting theory.

Curriculum Teaching and Research Based on Cloud Computing and Big Data

This study investigates the integrated application of cloud computing and big data in the field of education and its impact on curriculum teaching. Through a comprehensive review of the fundamental principles, current applications, and relevant literature, the study reveals the advantages and challenges of cloud computing and big data in aspects such as curriculum design, learning analytic, and personalized teaching. It also explores their influence on aspects like the sharing of teaching resources, the construction of online learning environments, and the evaluation of student learning outcomes. Furthermore, through case analysis and empirical studies, this paper provides a more in-depth validation of the practical effects of cloud computing and big data in improving teaching effectiveness, promoting educational innovation, and cultivating students’ information literacy. In summary, the integration of cloud computing and big data provides new perspectives and solutions for building smart education, while also laying a solid foundation for nurturing talents capable of meeting the demands of future society.

Magnetic-ferroelectric synergic control of multilevel conducting states in van der Waals multiferroic tunnel junctions towards in-memory computing.

van der Waals (vdW) multiferroic tunnel junctions (MFTJs) based on two-dimensional materials have gained significant interest due to their potential applications in next-generation data storage and in-memory computing devices. In this study, we construct vdW MFTJs by employing monolayer Mn2Se3 as the spin-filter tunnel barrier, TiTe2 as the electrodes and In2S3 as the tunnel barrier to investigate the spin transport properties based on first-principles quantum transport calculations. It is highlighted that apparent tunneling magnetoresistance (TMR) and tunneling electroresistance (TER) effects with a maximum TMR ratio of 6237% and TER ratio of 1771% can be realized by using bilayer In2S3 as the tunnel barrier under finite bias. Furthermore, the physical origin of the distinguished TMR and TER effects is unraveled from the k||-resolved transmission spectra and spin-dependent projected local density of states analysis. Interestingly, four distinguishable conductance states reveal the implementation of four-state nonvolatile data storage using one MFTJ unit. More importantly, in-memory logic computing and multilevel data storage can be achieved at the same time by magnetic switching and electrical control, respectively. These results shed light on vdW MFTJs in the applications of in-memory computing as well as multilevel data storage devices.

Cloud Computing Based Data Processing and Automated Management of Power Dispatch

Abstract As smart grids increase, the scope of power dispatch systems has broadened, encompassing not just traditional dispatch services but also multifaceted information services, encompassing data fusion, heterogeneous system integration, and big data analytics. However, managing intricate information businesses like big data analysis poses numerous challenges for the current power dispatch system, hindering its ability to keep up with escalating business demands. We introduce a cloud computing and big data analytics-based design scheme for a power dispatch data processing and automation management system to address this. Leveraging the distributed computing prowess of cloud computing platforms, the system ensures swift processing and analysis of vast power dispatch data. Additionally, by harnessing big data analysis techniques, the system delves into historical data, uncovers potential operational patterns and risk areas, and offers insights for optimizing the Electric Power System’s (EPS) operations. Experimental outcomes demonstrate the system’s remarkable proficiency in enhancing data processing, real-time control, and automation management capabilities, thereby bolstering the growth of intelligent power dispatch systems with robust technical backing.

ICT, Manufacturing and Industrial Automation of Biological Processes

The presence of wireless and mobile technologies in developing countries, the availability of low-cost, miniaturized wireless sensors, as well as the cost-efficient services provided by new hardware infrastructures have enabled new healthcare services, or new levels of quality and cost-efficiency in established ones. One crucial aspect of Healthcare 4.0 is the concept of P4 in Medicine: predictive, preventive, personalized and participatory. This approach, based on a comprehensive understanding of each patient biology, opposite to clustering patients into treatment groups, is being applied to reduce global health budgets by minimizing unnecessary use of drugs and procedures. These innovations come from the broad set of ICTs, and among them, the pillars of HC4.0 for their importance: IoT, Cloud Computing, and Big Data. Health 4.0 is used to improve the efficiency of physicians by enabling them to optimize resources and data availability. The future of health management will become timesaving and personalized as new technologies will empower individuals to conduct their health monitoring by using cyber–physical systems. Thanks to IoT, Cloud and Fog, as well as Big Data, researchers are allowed to design novel solutions, which are able to efficiently and effectively renew consolidated healthcare practices.

Building accurate numerical models

Numerical modeling has emerged as a crucial tool across various scientific and engineering disciplines, enabling the simulation and prediction of complex systems. This paper explores the comprehensive process of numerical model development, encompassing problem definition, mathematical formulation, discretization, implementation, and validation. High-performance computing (HPC) technologies, including supercomputers and parallel processing, play a pivotal role in managing large-scale simulations and enhancing computational efficiency. Key strategies such as algorithm optimization, parallel computing, and efficient data management are essential for maximizing computational resources. The integration of emerging technologies like machine learning, artificial intelligence, and quantum computing holds significant promise for advancing numerical modeling capabilities. Additionally, cloud computing offers scalable and flexible resources, making high-performance computing more accessible. The paper underscores the importance of continual refinement and validation of numerical models to maintain their accuracy and reliability, ultimately highlighting the dynamic and evolving nature of this critical scientific methodology.