In recent years, the Twin-Transition reference model has gained notoriety as one of the key options for decarbonizing the economy while adopting more sustainable models leveraged by the Industry 4.0 paradigm. In this regard, one of the most relevant...
Risk assessment of dam’s running status is an important part of dam management. A data-driven method based on monitored displacement data has been applied in risk assessment, owing to its easy operation and real-time analysis. However, previous...
The problem of cold-chain food safety is becoming increasingly prominent. Cold food chain risk assessment is an important way to ensure cold-chain food safety. Using CiteSpace, this study analyzes the knowledge map of research hotspots in the field o...
To enable proactive prediction of marine diesel engine failure time and root causes, thereby reserving sufficient time for maintenance, this study proposes a data-driven multi-algorithm integration framework for performance assessment and fault early...
Transient stability assessment (TSA) has always been a fundamental means for ensuring the secure and stable operation of power systems. Due to the integration of new elements such as power electronics, electric vehicles and renewable power generation...
Railway noise barrier constructions are subjected to high aerodynamic loads during the train passages, and the knowledge of their actual structural condition is relevant to assure safety for railway users and to create a basis for forecasting. This p...
Some grid-connected converters in practice are “black-box” devices with proprietary internal structures and parameters, rendering traditional model-based stability assessment infeasible. To address this issue, this paper proposes a data-d...
Given the pronounced impact COVID-19 continues to have on society—infecting 700 million reported individuals and causing 6.96 million deaths—many deep learning works have recently focused on the virus’s diagnosis. However, assessing...
The development of cross-border hydrogen energy value chains involves complex interactions between technological, regulatory, and logistical subsystems. Static assessment models often fail to capture the dynamic response of these coupled systems to e...
Air conditioners are a critical adaptation measure against heat- and cold-related risks under climate change. However, their electricity use and refrigerant leakage increase greenhouse gas (GHG) emissions. This study developed a data-driven life-cycl...
University admission exams can be understood as information systems in which subject areas act as components intended to convey predictive signals about students’ future academic performance. However, the informational effectiveness of these su...
For the requirements of performance assessment of the thermal power plant control process, the combustion control system of a 330 MW generator unit in a power plant is studied. Firstly, the five variables that affect the process control performance a...
The higher education (HE) system is witnessing immense transformations to keep pace with the rapid advancements in digital technologies and due to the recent COVID-19 pandemic compelling educational institutions to completely switch to online teachin...
The growing demand for sustainable development has exposed significant limitations in how Higher Education Institutions (HEIs) evaluate sustainability-oriented research, particularly due to fragmented indicators, descriptive approaches, and the absen...
Plant wearable sensors can resolve physiological responses that soil, weather, and canopy observations capture only indirectly. This critical narrative review evaluates optical, electrochemical, electrical, mechanical, thermal, and acoustic platforms...
Infrastructure projects that transform ecosystems and landscapes, such as hydropower developments, are essential for economic growth but pose significant socio-environmental challenges. Addressing these complexities requires advanced, dynamic managem...
AI-driven digitalisation transforms how organisations process personal data and introduces risks that traditional Data Protection Impact Assessment (DPIA) frameworks cannot adequately address. Automated decision-making and large-scale processing in A...
The aircraft critical system’s health state will affect flight safety dramatically, such as flight control system, and its health state awareness or assessment is very important to avoid flight accident. A data-driven health assessment based on...
Data-driven organizations aim to control business decisions based on data. However, despite significant investments in digitalization, studies show that many organizations continue to face challenges in fully realizing the benefits of data. Existing...
Credit risk refers to the possibility of borrower default, and its assessment is crucial for maintaining financial stability. However, the journey of credit risk data generation is often gradual, and machine learning techniques may not be readily app...
Susceptibility assessment is a crucial task for mitigating landslide hazards. It includes displacement prediction, stability analysis, and location prediction for individual hillslopes or regional mountainous areas. Physically based models can assess...
Data-driven manufacturing in Industry 4.0 demands digital metrology not only to drive the in-process quality assurance of manufactured products but also to supply reliable data to constantly adjust the manufacturing process parameters for zero-defect...
Total Cloud Cover (TCC) retrieval from ground-based optical imagery is a problem that has been tackled by several generations of researchers. The number of human-designed algorithms for the estimation of TCC grows every year. However, there has been...
Sustainable urban mobility is gaining importance as cities seek to address congestion and environmental concerns, with cycling infrastructure being an essential component of urban transportation systems. This study proposes a novel integrated, data-d...
Contemporary security competition is increasingly characterized by complex interactions across political, economic, military, and cultural domains, with countries employing combinations of cross-domain strategic options to achieve their objectives. E...
With the interconnection between large power grids, the issue of security and stability has become increasingly prominent. At present, data-driven power system adaptive transient stability assessment methods have achieved excellent performances by ba...
20 September 2018
In recent decades, many researchers have focused on the issue of medical failures in the healthcare industry. A variety of techniques have been employed to assess the risk of medical failure and to generate strategies to reduce the frequency of medic...
Under the typhoon disaster, the power grid often has serious accidents caused by falling power towers and breaking lines. It is of great significance to analyze and predict the damage probability of a transmission line-tower system for disaster preve...
Under the background of urban stock renewal, the quality improvement of public spaces in aged residential areas is confronted with challenges such as inefficient data collection, disconnection between subjective and objective evaluations, and insuffi...
Flexible automated assembly lines (FAALs) in Industry 4.0 require robust quality management that integrates operational data with systematic risk analysis. However, Process Failure Mode and Effects Analysis (PFMEA) documents are often developed durin...
Quality assessment of public spaces is critical in sustainably enhancing urban spatial quality. Existing studies focus on fundamental indicators (e.g., geographic accessibility, planning rationality, and social benefits) and often rely on geographic...
In group management, accurate assessment of individual performance is crucial for the fair allocation of resources such as bonuses. This paper explores the complexities of gauging each participant’s contribution in multi-participant projects, p...
Assessing leakage risks in water distribution networks (WDNs) and implementing preventive monitoring for high-risk pipelines has become a widely accepted approach for leakage control. However, existing methods face significant data barriers between G...
Quality assurance (QA) in higher education has become increasingly vital in response to global competition, digital transformation, and evolving sustainability demands. This study examines the leading QA frameworks—namely the European Standards...
River health assessment frameworks play a critical role in guiding restoration planning and watershed management, yet conventional index-based approaches often rely on fixed weighting schemes that limit diagnostic sensitivity and interpretability. Th...
Parkinson’s disease (PD) is characterized by motor symptoms, with key diagnostic features, such as rigidity, traditionally assessed through subjective clinical scales. This study proposes a novel hybrid framework integrating model-driven biomec...
Unmanned autonomous systems (UASs), including drones and robotics, are widely employed across various fields. Despite significant advances in AI-enhanced intelligent systems, there remains a notable deficiency in the interpretability and comprehensiv...
European cities are under pressure to be at the forefront of climate neutrality while providing inclusive, safe, and sustainable urban mobility. Street experiments are being adopted to accelerate this transition, yet assessing their impact remains ch...
Understanding the seasonal behaviour of sewer failures is essential for infrastructure reliability and sustainable asset management. This study presents a seasonality-centred, data-driven analysis of monthly sewer failures over a 15-year period (2010...
On becoming a commodity, Microgrids (MGs) have started gaining ground in various sizes (e.g., nanogrids, homegrids, etc.) and forms (e.g., local energy communities) leading an exponential growth in the respective sector. From demanding deployments su...
Shallow landslides are very dangerous phenomena, widespread all over the world, which could provoke significant damages to buildings, roads, facilities, cultivations and, sometimes, loss of human lives. It is then necessary assessing the most prone z...
Cultural tourism (CT) has emerged as a critical driver of destination competitiveness; however, stakeholders struggle to balance heritage preservation, sustainable growth, and visitor management. Current decision making often lacks the practical info...
Post-disaster flood risk assessment is extremely difficult owing to the great uncertainties involved in all parts of the assessment exercise, e.g., the uncertainty of hydrologic–hydraulic models and depth–damage curves. In the present stu...
The assessment of buildings’ energy performance plays a critical role in achieving global sustainability goals, particularly in reducing carbon emissions and improving energy efficiency. In this context, various modelling approaches have been d...
As global warming continues to intensify, typhoon disasters will more frequently occur in East and Southeast Asia, posing a high risk of causing large-scale power outages in the power system. To investigate the impact of typhoon disasters on high-vol...
Artificial intelligence (AI) is a scientific and engineering discipline that involves designing systems capable of autonomously replicating the cognitive functions typically associated with human intelligence. Current AI uses data to extract patterns...
This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this s...
This paper presents a case study framework for the operational reliability monitoring of a grid-connected photovoltaic (PV) inverter using SCADA measurements collected during February–April 2025. The workflow combines correlation-based drift an...
The availability of building operational data such as energy use and indoor temperature provides opportunities to enhance the traditional building energy performance calculation. Disaggregated building energy use facilitates informed decision-making...
To improve the physical consistency and interpretability of traditional drought indices, this study proposes a drought assessment model that couples physically based constraints with data-driven approaches, leading to the development of a Multivariat...
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