Sustainable machining of composite materials requires optimizing conflicting responses influenced by limited experimental datasets, trade-offs, nonlinear process variables, and response variability. This study proposes a hybrid framework (Gaussian Pr...
This study investigated the optimization and quality evaluation of green tea infusions prepared from three commercial green tea samples from different production origins, namely Anhui Huangshan Maofeng (AH), Shaanxi Ziyang (SX), and Yunnan Xuelong (Y...
The structural safety and performance of long-span bridges in coastal areas are significantly influenced by the wind field. Traditional univariate or simplified multivariate probabilistic models often fail to capture the multimodal and nonlinear depe...
Tech mining is an analytical method of technology monitoring that can reveal technology trends in different industries. Patent databases are the major sources for information retrieval by tech mining methods. The majority of the commercially viable r...
This study develops an integrated generative artificial intelligence (GAI) framework for improving business process performance in industrial enterprises. The framework treats GAI not as the isolated use of generative tools, but as a governable infor...
Business analytics increasingly relies on analytical performance models to support real-time, data-driven decision-making in multi-stage service processes. Discrete-event simulation and process mining offer valuable insights but face scalability and...
Monitoring agricultural drought is crucial for mitigating yield losses in winter wheat, especially in the Huang-Huai-Hai (HHH) region of China. Current drought indices often fall short in accurately representing the water supply–demand dynamics...
The effective representation of land surface hydrological models strongly relies on spatially varying parameters that require calibration. Well-calibrated physical models can effectively propagate observed information to unobserved variables, but tra...
Universities increasingly rely on stakeholder engagement to advance sustainability. However, existing sustainability assessment frameworks often overlook how stakeholder influence varies across institutional processes. This study develops a conceptua...
Evolving fuzzy systems (EFS) offer an incremental learning, making them promising for fault diagnosis (FD) in industrial processes, where unknown faults and changing operation conditions are common. The evolving fuzzy structure enables incremental ru...
This paper proposes a design-technology co-optimization (DTCO) framework applicable to advanced technology nodes, which accelerates the process optimization exploration for such nodes. Developing automatic parameter extraction algorithms tailored for...
In the era of data-driven technologies, the need for diverse and high-quality datasets for training and testing machine learning models has become increasingly critical. In this article, we present a versatile methodology, the Generic Methodology for...
The process monitoring method for industrial production can technically achieve early warning of abnormal situations and help operators make timely and reliable response decisions. Because practical industrial processes have multimodal operating cond...
With the aggressive scaling of feature size, Negative Bias Temperature Instability (NBTI) and Process Variation (PV) have become major issues for circuit reliability and yield. In this paper, we analyze the variation of gate delay by jointly consider...
Ensuring consistent quality and safety in agri-food processing is a strategic priority for firms seeking compliance with international standards such as ISO 9001 and ISO 22000. Traditional inspection practices in Ecuador’s food industry remain...
This paper considers a dynamical way to connect resilience outcomes and processes by nesting process-based approaches inside a controlled dynamical system under resource constraints. To illustrate this, we use a dynamical model of electric power gene...
Multi-response optimization problems investigation is a crucial element in initiatives designed to enhance quality and overall productivity for manufacturing processes. Since no particular algorithm can be employed for all multi-response problems, de...
A warming climate will intensify the water cycle, resulting in an exacerbation of water resources crises and flooding risks in the Lancang–Mekong River Basin (LMRB). The mitigation of these risks requires accurate streamflow and flood simulatio...
Access to a reliable and safe domestic water supply is a serious challenge for many developing countries worldwide. In the capital of Vietnam, Hanoi, the municipal government is facing a number of difficulties in providing sufficient water in a susta...
The gap between development of effective physical activity interventions and the wide-scale adoption of these interventions in real-world settings has been reported since the early 2000s. Evaluations have been criticised for failing to report details...
Training interoceptive sensitivity (IS) might be a first step in effectively promoting intuitive eating (IE). A dyadic interoception-based pilot randomized controlled trial was conducted to increase IE among couples aged 50+. The training consisted o...
Complex and long interactions (e.g., a change of topic during a conversation) justify the use of dialog systems to develop task-oriented chatbots and intelligent virtual assistants. The development of dialog systems requires considerable effort and t...
In the context of developing PINN methods for real-time digital twins in manufacturing processes, we propose a new approach that combines two complementary weighting strategies to significantly improve their convergence. The first method, called SD-P...
Solid-state batteries (SSBs) present a promising advancement in energy storage technology, with the potential to achieve higher energy densities and enhanced safety compared to conventional lithium-ion batteries. However, their commercialisation is h...
Due to increasingly stringent legal requirements and escalating environmental control costs, chemical industries have paid close attention to sustainable development without compromising their economic performance. Thus, chemical industries are in ne...
Computer vision (CV)-based recognition approaches have accelerated the automation of safety and progress monitoring on construction sites. However, limited studies have explored its application in process-based quality control of construction works,...
User-based collaborative filtering is one of the most-used methods for the recommender systems. However, it takes time to perform the method because it requires a full scan of the entire data to find the neighboring users of each active user, who hav...
With the growing awareness regarding the importance of personal data protection, many countries have established laws and regulations to ensure data privacy and are supervising managements to comply with them. Although various studies have suggested...
Soil and groundwater systems have natural attenuation potential to degrade or detoxify contaminants due to biogeochemical processes. However, such potential is rarely incorporated into active remediation strategies, leading to over-remediation at man...
To address the multi-objective optimization of stamping process parameters for vehicle components, a hybrid framework coupling Dynaform simulations, Orthogonal Experimental Design, BPNN, NSGA-II, and TOPSIS was proposed. Taking car door accessories a...
This study examines how a visitor-centered approach enhances engagement, participation, and intangible heritage transmission to support cultural sustainability in ethnographic museums. We conducted online and on-site behavioral observations, question...
Coastal regions concentrate livestock and fisheries activities that generate large volumes of organic residues, often managed inadequately and contributing to nutrient loading, soil degradation, and marine pollution. At the same time, these territori...
Service robots operating in indoor environments should recognize dynamic changes from sensors, such as RGB-depth (RGB-D) cameras, and recall the past context. Therefore, we propose a context query-processing framework, comprising spatio-temporal robo...
Sustainability study of the standard wastewater treatment system is the pivotal procedure in the water protection field. In order to better study the sustainability of sewage treatment systems, wastewater treatment system of straw pulp papermaking (W...
This study proposes a Client-Fog-Cloud (CFC) multilayer data processing and aggregation framework that is designed to promote latency-sensitive applications in an IoT context. The framework is designed to address the current IoT-based challenges: wid...
There is an increasing demand for processing large volumes of unstructured data for a wide variety of applications. However, protection measures for these big data sets are still in their infancy, which could lead to significant security and privacy...
Third-wave cognitive-behavioral therapies (CBT3) have progressively shifted the focus of psychotherapy from symptom reduction to process-based and transdiagnostic mechanisms of change, emphasizing self-identification as a core dimension. Within this...
Currently, the manufacturing industry is experiencing a data-driven revolution. There are multiple processes in the manufacturing industry and will eventually generate a large amount of data. Collecting, analyzing and storing a large amount of data a...
Recently, a shift from substance-based to process-based ontologies of living beings and biological entities has been widely advocated, largely on the grounds that traditional substance thinking, by encouraging biological reductionism, fails to adequa...
Climate change and human activities are intensifying the hydrologic cycle and increasing extreme events, challenging accurate prediction. This study builds on the Transformer architecture by introducing a sliding time window and runoff classification...
The literature on capital allocation is biased towards an asset modeling framework rather than an actuarial framework. The asset modeling framework leads to the proliferation of inappropriate assumptions about the effect of insurance line of business...
Listeria monocytogenes poses a significant risk in meat-processing plants, especially in micro and small businesses, where structural, organisational and operational limitations make it difficult to control. Although there is evidence of its environm...
In industrial vehicle design processes, most companies have implemented model-based systems engineering (MBSE). As a consequence, design processes are nowadays not driven by documents, but by digital models of the vehicle to be developed and its comp...
Treatment of nitrate rich groundwater using permeable reactive barriers (PRBs) established with injection of emulsified vegetable oil is receiving attention in areas where groundwater discharges contribute to eutrophication (e.g., Cape Cod, MA). To b...
Digital Twin (DT) technology has evolved to contextualize real-time interactions between the physical and digital worlds. It has gained increasing attention in various research areas and industries, including the manufacturing, aerospace, and automot...
This study establishes a closed-loop chain of evaluation, optimization, and capability assessment for the hot stamping of 1.2 mm B1500HS ultra-high-strength steel. A four-dimensional quality framework (appearance, geometry, mechanics and microstructu...
The current debate on urban regeneration highlights the significance of social innovation and the reuse of cultural heritage to develop new economic and entrepreneurial models, creating value chains and benefits for communities. International and Eur...
With the evolution of traditional production towards smart manufacturing, humans and machines interact dynamically to handle complex production systems in semi-automated environments when full automation is not possible. To avoid undesirable side eff...
This paper proposes an applied framework for cyberattack and anomaly detection in resource-constrained embedded/IoT environments by combining signal-processing feature construction with supervised and unsupervised AI (Artificial Intelligence) models....
The early detection and spatial characterization of crop damage are critical for improving decision-making in precision agriculture, particularly in regions where traditional monitoring methods are limited in scalability and objectivity. This study p...
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