Taking the dynamic capability theory as the research framework, using a two-stage questionnaire survey and 318 Chinese enterprises as samples, this study investigates the impact mechanism of big data technical skills on novel business model innovatio...
The transformative potential of Artificial Intelligence (AI) in urban management is severely constrained by pervasive systemic fragmentation. While AI applications demonstrate high efficacy within isolated domains, they rarely achieve the cross-domai...
The construction industry accounts for approximately 13% of global GDP but suffers from chronic productivity stagnation. Although artificial intelligence (AI) offers transformative potential, its adoption is constrained by three key barriers: data in...
As a key enabling technology for energy transition, the smart grid is propelling the global power system to evolve toward greater efficiency, reliability, and sustainability. Based on the three-dimensional analysis framework of “technology&ndas...
The integration of Building Information Modeling [BIM] and Digital Twins [DT] has emerged as a central driver of digital transformation in the architecture, engineering, and construction sector. Yet, its systemic impact remains constrained by concept...
The raising accessibility of Unmanned Aerial Vehicles (UAVs), colloquially known as drones, is rapidly increasing. Recent studies have discussed challenges that may come in tow with the growing use of this technology. These studies note that in-depth...
The rapid expansion of Artificial Intelligence is fueling the growth of hyperscale data centers, which introduces significant challenges to existing power systems. This paper aims to provide a comprehensive survey of these integration challenges, spe...
Background: Monitoring training load and recovery is essential for performance optimization and injury prevention in youth football. However, predicting subjective recovery in preadolescent athletes remains challenging due to biological variability a...
The demand for water is constantly increasing, while there are factors related to climate change and pollution that make it less and less available. Addressing this problem means being able to face it with a global approach, which takes into account...
Preserving and managing historical cultural heritage necessitates innovative approaches that harmonize technology with historical documentation. This paper presents a case study showcasing an adaptable online database tailored for the incorporation o...
The digitalization of farming is considered the fourth revolution in agriculture. The necessity of providing decision support tools and electronic platforms to help Greek farmers in their work is becoming increasingly evident. For this reason, this a...
Thermography provides non-invasive, radiation-free diagnostic imaging. Despite the extensive literature on medical thermography, a comprehensive overview of current applications is lacking. Hence, the aim of this scoping review is to identify the med...
Forecasting stock markets is challenging due to the influence of various internal and external factors compounded by the effects of globalization. This study introduces a data-driven approach to forecast S&P 500 returns by incorporating macroecon...
In this paper, we establish the existence and stability results for the
Big Data Analytics (BDA) has evolved from a predominantly technical batch function into a socio-technical capability integrating cloud-native platforms, stream processing, Lakehouse architecture, machine learning operations (MLOps), visualization, go...
This study examines Lean 4.0, defined as the integration of Lean soft practices (LSPs) and Industry 4.0 technologies (I4Ts), from a socio-technical systems perspective. While prior research has mainly linked Lean and I4Ts to operational and cost-base...
Technical systems generate an increasing amount of data as integrated sensors become more available. Even so, data are still often scarce because of technical limitations of sensors, an expensive labelling process, or rare concepts, such as machine f...
Stock market prediction is a subject of great interest within the finance industry and beyond. In this context, our research investigates the use of reinforcement learning through implementing the double deep Q-network (DDQN) alongside technical indi...
Ensuring high-quality and uninterrupted power supply to consumers is one of the main problems of creating reliable power systems of a new generation. It is associated with the implementation of an integral assessment of the technical state of equipme...
Digital twins (DTHs) and virtual twins (VTHs) in healthcare represent emerging technologies towards precision medicine, providing opportunities for patient-centric healthcare. Our scoping review aimed to map the current DTH and VTH technologies in on...
Research Purpose: This study investigates the role of digital investor behavior, measured through Google Trends, alongside technical indicators such as RSI and Bollinger Bands, in forecasting volatility in the Dubai Financial Market. The aim is to de...
While Integrated Pest Management (IPM) is a sustainable approach of pest control, contributing to reduced use of pesticides and risks on human health and the environment, farmers have shown limited interest in practicing this method. The present stud...
Industrial data products create economic value through embodied technical resources, current decision use, and future deployment rights. This article develops a Cost–Premium Valuation System (CPVS) that measures these channels as a quality-adju...
Carbon Capture and Storage (CCS) technology presents a practical solution for reducing industrial carbon dioxide (CO2) emissions through underground anthropogenic CO2 storage in depleted hydrocarbon reservoirs. The long-term storage efficiency faces...
This study investigates the integration of Large Language Models (LLMs) into supply chain workflow automation, with a focus on their technical, operational, financial, and socio-technical implications. Building on Dynamic Capabilities Theory and Soci...
Background: Human care represents the essence of nursing but faces challenges from increasing technological advancement and healthcare system bureaucratization. Objective: To understand how nursing students balance technical demands with human aspect...
Integrating best management practices and improving the technical efficiency of smallholder maize farmers is critical in raising overall agricultural output. However, there is not much information, besides marginalization and high rehabilitation and...
Geometallurgy is an important addition to any evaluation project or mining operation. As an integrated approach, it establishes 3D models which enable the optimisation of net present value and effective orebody management, while minimising technical...
In this article we critically discuss the challenge of integrating contextual information, in particular spatiotemporal contextual information, with human and technical sensor information, which we approach from a geospatial perspective. We start by...
Accurately predicting stock prices remains a challenging task due to the volatile and complex nature of financial markets. In this study, we propose a novel hybrid deep learning framework that integrates a large language model (LLM), a Linear Transfo...
In recent years, there has been a notable increase in the integration of technology and the employment of technological experts within newsrooms. However, there remains a paucity of scholarly research examining the evolution and maturation of these p...
The guidelines to the Public Sector Information (PSI) Directive states: “opening up public sector information (PSI) for reuse brings major socioeconomic benefits”, which has been recognised in various domains. However, the reuse may be li...
The reconstruction of historic buildings requires the integration of diverse data sources, both geometric and non-geometric. This study presents a multi-source data analysis methodology for heritage reconstruction using 3D modeling and Historic Build...
Blockchain is a distributed database technology that enables immutable, verifiable data recording, properties that are useful for failure analysis processes requiring high data integrity and traceability. In conveyor belt failure analysis, there is a...
This review discusses the transformative potential of integrating multi-omics data and artificial intelligence (AI) in advancing horticultural research, specifically plant phenotyping. The traditional methods of plant phenotyping, while valuable, are...
This study provides a technology-level reference for the future development, implementation, and validation of intelligent O&M systems for high-end drilling equipment. Intelligent operation and maintenance systems for high-end drilling equipment...
Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate...
Integrated solutions to groundwater management problems require effective analysis of stream-aquifer connections, especially in irrigated semi-arid regions where groundwater pumping affects return flows and causes streamflow depletion. Scientific res...
Recent breakthroughs in machine learning, artificial intelligence, and the emergence of large datasets have made the integration of eye tracking increasingly feasible not only in computing but also in many other disciplines to accelerate innovation a...
During scientificstudies on reciprocating self-ignition marine engines, varying data are often needed. Such data are often in various collections and obtaining some of these is very difficult. Therefore, as it was elaborated in the electronic databas...
Data quality is fundamental to scientific integrity, reproducibility, and evidence-based decision-making. Nevertheless, many datasets lack transparency in their collection and curation, undermining trust and reusability across research domains. This...
Urban public transport systems are complex socio-technical ecosystems whose maturity depends not only on fleet and infrastructure quality, but also on operational coordination, data use, disruption response, and service continuity. The model integrat...
Decentralised renewable energy (RE) systems such as solar PV mini-grids (MG) are considered to be a cornerstone for the strategic achievement of the UN’s energy access goals in the developing world. Many of these systems implemented however face subs...
Integrated land–soil–crop information systems are increasingly important for supporting climate-smart agricultural planning and implementation, yet their development in Eastern Africa is constrained by fragmented mandates, weak technical...
This paper presents a novel method for assessing the technical condition of devices in the high-voltage (HV) switching bay of a substation, focusing on circuit breakers, disconnectors, and instrument transformers. These devices are typically maintain...
The stock market represents one of the most complex mechanisms in the financial world. It can be seen as a living being with complex ways to enact, interact, evolve, defend, and respond to various stimuli. Technical analysis is one of the most comple...
Hydrogen production from waste plastics is emerging as a potential low-carbon pathway that integrates waste management with energy production. This study develops an integrated socio-technical framework combining a comparative assessment of thermoche...
Stock market predictions are a challenging problem due to the dynamic and complex nature of financial data. This study proposes an approach that integrates the domain knowledge of investors with a long-short-term memory (LSTM) algorithm for predictin...
Background: Post-surgical cardiovascular monitoring places a heavy information burden on clinical teams, requiring the rapid synthesis of patient history, intraoperative data, monitoring streams, and surgical outcome evidence. Existing clinical decis...
The problem of stock price prediction has been a hot research issue. Stock price is influenced by various factors at the same time, and market sentiment is one of the most critical factors. Financial texts such as news and investor comments reflect i...
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