Hierarchical stochastic processes, such as the hierarchical Dirichlet process, hold an important position as a modelling tool in statistical machine learning, and are even used in deep neural networks. They allow, for instance, networks of probabilit...
As the adoption of information technologies increases in the manufacturing industry, manufacturing companies should efficiently manage their data and manufacturing processes in order to enhance their manufacturing competency. Because smart factories...
With the continuous complexity and frequent changes in business application scenarios, companies urgently need to establish a flexible business process management mechanism that includes dynamic rules, in which dynamic adaptation methods of business...
Forecasting often involves multiple time-series that are hierarchically organized (e.g., sales by geography). In that case, there is a constraint that the bottom level forecasts add-up to the aggregated ones. Common approaches use traditional forecas...
This research proposes a hierarchical aggregation approach using Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) for indicators. The core logic of the proposed approach is to reflect the hierarchical structures of indicators and...
The accurate cycle time (CT) prediction of the wafer fabrication remains a tough task, as the system level of work in process (WIP) is fluctuant. Aiming to construct one unified CT forecasting model under dynamic WIP levels, this paper proposes a tra...
Wetting has been studied in various fields: chemical industry, automobile manufacturing, food companies, and even life sciences. In these studies, super-hydrophobic surfaces have been achieved through complex steps and processes. To realize super-hyd...
Aiming at the general integrated scheduling problem of tree-structured complex single-product machining and assembling, a reverse order hierarchical integrated scheduling algorithm (ROHISA) is proposed by considering the dynamic time urgency degree (...
Hierarchical porous silicon carbide (SiC) attracts great attention due to its superior chemical resistance, high thermal shock resistance, and excellent thermal stability. The preparation of a porous SiC monolith via a simple sol–gel method is...
Accurate and real-time quality prediction to realize the optimal process control at a competitive price is an important issue in Industrial 4.0. This paper shows a successful engineering application of how smart soft sensors can be combined with mach...
Mobile robots are faced with problems (for ex. path planning) with many alternative solutions (ex. paths) based on several factors, and they must make a selection by quantifying the factors and mathematically evaluating the alternative solutions. Rob...
This work presents a hierarchical deep reinforcement learning (DRL) framework based on Soft Actor–Critic (SAC) for the autonomy of rock-breaking machinery in surface mining comminution processes. The proposed approach explicitly integrates mobi...
Satellite-based aerosol optical depth (AOD) data are widely used to estimate land surface
Hierarchical Bayesian models based on Gaussian processes are considered useful for describing complex nonlinear statistical dependencies among variables in real-world data. However, effective Monte Carlo algorithms for inference with these models hav...
The problem of choosing an electric generator in order to increase the reliability and continuity of energy supply to households in Ukraine was considered. It was shown that this choice is made under conditions of uncertainty. The methods of choosing...
We propose two Mann-type subgradient-like extra gradient iterations with the line-search procedure for hierarchical variational inequality (HVI) with the common fixed-point problem (CFPP) constraint of finite family of nonexpansive mappings and an as...
Various studies have confirmed that the increasing quality of safety climate has a positive influence on reducing the occurrence of accidents. The quality of safety climate is comprehensively affected in three domains: management, site, and enterpris...
An advanced model-based control method for the integrated fuel processing and a fuel cell system consisting of ethanol reforming, hydrogen purification, and a proton exchange membrane fuel cell is presented. For process identification, a physical mod...
Effective requirement collection and prioritization are paramount within the inherently distributed nature of the Internet of Things (IoT) application. Current methods typically categorize IoT application requirements subjectively into inessential, d...
Mining plays a pivotal role in economies worldwide, contributing to employment, infrastructure, and the supply of essential raw materials. Chile’s global mining powerhouse, particularly in copper production, exemplifies this industry’s ec...
Economic, social and governance (ESG) have become topical subjects amidst the deleterious effects of climate change, inequality and similar pressing challenges facing the people and the planet. The main objective of this study was to rank the importa...
Hierarchically structured silicon (Si) surfaces with a combination of micro/nano-structures are highly explored for their unique surface and optical properties. In this context, we propose a rapid and facile electroless method to realize hierarchical...
Exploring alternative freshwater resources other than those surrounding the Nile is critical to disperse Egypt’s population to other uninhabited desert areas. This study aims to locate groundwater potential zones (GWPZs) in the water-scarce des...
Hierarchical micro/-nanostructures were produced on polycarbonate polymer surfaces by employing a two-step UV-laser processing strategy based on the combination of Direct Laser Interference Patterning (DLIP) of gratings and pillars on the microscale...
The exploitation potential of shallow geothermal energy is usually defined in terms of site-specific ground thermal characteristics. While true, this assumption limits the complexity of the analysis, since feasibility studies involve many other compo...
The study of the human visual system not only helps to understand the mechanism of the visual system but also helps to develop visual aid systems to help the visually impaired. As the systematic study of neural signal processing mechanisms in early b...
Ti-6242 is a near alpha titanium alloy, which has excellent high-temperature creep resistance and is widely used in jet engine compressors. This alloy is susceptible to creep fatigue failure under dwell loading below 473 K. The existence of microtext...
Federated learning (FL) has emerged as a promising solution for the Internet of Things (IoT), facilitating distributed artificial intelligence while ensuring communication efficiency and data privacy. Traditional methods involve transmitting raw sens...
Cameras are widely adopted for high image quality with the rapid advancement of complementary metal-oxide-semiconductor (CMOS) image sensors while offloading vision applications’ computation to the cloud. It raises concern for time-critical applicati...
The precise categorization of brief texts holds significant importance in various applications within the ever-changing realm of artificial intelligence (AI) and natural language processing (NLP). Short texts are everywhere in the digital world, from...
Image has been widely accepted as a combination of perceived elements that are commonly discrete and static ones. ‘Discrete’ means that the elements are treated as separate ones with each other, with no interactions among them. ‘Static’ means that th...
Communication in noise is a complex process requiring efficient neural encoding throughout the entire auditory pathway as well as contributions from higher-order cognitive processes (i.e., attention) to extract speech cues for perception. Thus, ident...
In the field of infrastructure construction, progress in digital transformation remains limited; this is particularly true in road construction, an infrastructure facility involving design, construction, and operation stages. Many construction subjec...
The influence of ultra-short laser modification on the surface morphology and possible chemical alteration of poly-lactic acid (PLA) matrix in respect to the optimization of cellular and antibacterial behavior were investigated in this study. Scannin...
The influence of residual cuts on the deactivation of hierarchical Y zeolite-based catalysts during the co-processing of vacuum gas oil (VGO) with atmospheric residue (ATR) was investigated. The experiments were conducted in a laboratory-scale MAT-ty...
In this work, MnZn ferrite nanoparticles with hierarchical morphology were synthesized hydrothermally, and their surface characteristics were improved by the PEGylation process. In vitro MRI studies were also conducted to evaluate the ability of the...
Hierarchy analysis of the knowledge graphs aims to discover the latent structure inherent in knowledge base data. Drawing inspiration from topic modeling, which identifies latent themes and content patterns in text corpora, our research seeks to adap...
Hierarchical surface structures were fabricated on fused silica by using a fs-laser with a pulse duration τ = 300 fs and a wavelength λ = 512 nm. The resulting surface structures were characterized by scanning electron microscopy, atomic f...
The capability of efficiently processing the data streams emitted by nowadays ubiquitous sensing devices enables the development of new intelligent services. Data Stream Processing (DSP) applications allow for processing huge volumes of data in near...
This study introduces a novel two-stage model for assessing and enhancing business excellence based on the EFQM framework. The Fuzzy Analytic Hierarchy Process (FAHP) is used in the first stage to calculate the weight vectors of criteria and sub-crit...
This study compared hierarchical Bayesian, mixed-effects Gaussian process regression, and random forest models for predicting height to crown base (HCB) in Qinghai spruce (Picea crassifolia Kom.) forests using LiDAR-derived data. Both modeling approa...
Concept drift, which refers to changes in the underlying process structure or customer behaviour over time, is inevitable in business processes, causing challenges in ensuring that the learned model is a proper representation of the new data. Due to...
Modern mineral processing plants utilise fault detection and diagnosis to minimise time spent under faulty conditions. However, a fault originating in one plant section (PS) can propagate throughout the entire plant, obscuring its root cause. Causali...
The study proposes a model for the deposition of coatings, which takes into account the stochastic nature of the deposition process and is built considering the influence of the parallel convection and diffusion processes. The investigation has found...
We examine issues of prior sensitivity in a semi-parametric hierarchical extension of the INAR(p) model with innovation rates clustered according to a Pitman–Yor process placed at the top of the model hierarchy. Our main finding is a graphical...
In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt) process regression model that assumes a MaxEnt prior distri...
This research is concerned with a methodology for automated generation of polyhedral building models for complex structures, whose rooftops are bounded by straight lines. The process starts by utilizing LiDAR data for building hypothesis generation a...
Point-like targets are useful in providing surface deformation with the time series of synthetic aperture radar (SAR) images using the multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology. However, the spatial density of poin...
Process planning is a typical combinatorial optimization problem. When the scale of the problem increases, combinatorial explosion occurs, which makes it difficult for traditional precise algorithms to solve the problem. A hybrid particle swarm optim...
Recent advancements in multimodal large language models (MLLMs) have demonstrated remarkable capabilities in processing diverse data types, yet significant disparities persist between human cognitive processes and computational approaches to multimod...
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