Sequential recommender models should capture evolving user preferences over time, but there is a risk of obtaining biased results such as false positives and false negatives due to noisy interactions. Generative models effectively learn the underlyin...
Sequential experimental designs enhance data collection efficiency by reducing resource usage and accelerating experimental objectives. This paper presents a model-driven approach to sequential Latin hypercube designs (SLHDs) tailored for second-orde...
The matrix converter (MC) is a promising converter that performs the direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful tool for power electronic converters, including the MC. However, weighting factor design and heav...
The use of electrical energy is directly proportional to the increase in global population, both concerning growing industrialization and rising residential demand. The need to achieve a balance between electrical energy production and consumption in...
Experimental optimization with surrogate models has received much attention for its efficiency recently in predicting the responses of the experimental optimum. However, with the development of multi-fidelity experiments with surrogate models such as...
Traditional sequential recommender systems have primarily relied on implicit pattern recognition in user interaction sequences, achieving strong performance but functioning as “black boxes” that lack transparent reasoning. This paper intr...
In recent years, organizations have increasingly become aware of the importance of employee happiness as well as the role of HRM practices and personal resources in promoting well-being at work. Based on the Job Demand–Resources model, we inves...
IoT plays an important role in daily life; commands and data transfer rapidly between the servers and objects to provide services. However, cyber threats have become a critical factor, especially for IoT servers. There should be a vigorous way to pro...
This work presents an alternating sequential model predictive control (ASMPC) scheme applied to multimodular matrix converters. The proposed strategy alternately evaluates two control objectives: load current tracking and input reactive power minimiz...
Finite Set Model Predictive Control (FS-MPC) is a widely used technique in power electronic converter applications. One challenge in FS-MPC implementation is selecting appropriate weighting factors, as there is currently no established methodology fo...
Surrogate Modeling (SM) is often used to reduce the computational burden of time-consuming system simulations. However, continuous advances in Artificial Intelligence (AI) and the spread of embedded sensors have led to the creation of Digital Twins (...
Since the inauguration of the government-led five year economic plans in the 1960s, Korea has achieved remarkable economic development. Korea’s economic strategy, known as ‘The Miracle on the Han River’, focused on heavy and chemical industries such...
By virtue of the advances in sensing techniques, finite element (FE) model updating (FEMU) using static and dynamic data has been recently employed to improve identification on updating parameters. Using heterogeneous data can provide useful informat...
Marine velocity-model building using full-waveform inversion (FWI) is strongly affected by acquisition geometry because different surveys sample different parts of the wavefield. In this study, we investigate a sequential OBS (ocean-bottom seismomete...
21 May 2021
The lack of an efficient approach in managing pharmaceutical prices in the procurement system led to a substantial burden on government budgets. In Thailand, although the reference price policy was implemented to contain the drug expenditure, there h...
The purpose of this study was to examine, using a sequential model, factors associated with volunteer participation and sleep efficiency in Japanese older adults receiving treatment for hypertensive disease. A questionnaire survey was conducted to co...
Objective: Employ the hollow fiber infection model (HFIM) to study sequential antibiotic administration (ampicillin, ciprofloxacin and fosfomycin) using human pharmacokinetic profiles to measure changes in the rate of antibiotic resistance developmen...
Periodontal therapies use immune mediators, but their side effects can increase with dosage. Micro-immunotherapy (MI) is a promising alternative that employs immune regulators at low and ultralow doses to minimize adverse effects. In this study, the...
Dysregulated hepatic cholesterol handling and oxidative stress represent key targets for nutritional interventions. This study investigated a combination of Ophiocordyceps sinensis (formerly Cordyceps sinensis) extract and coenzyme Q10 (CoQ10) using...
Environmental degradation is no longer a distant threat; it now permeates social media feeds, casual conversations, and daily digital content. However, whether incidental exposure to environmental news leads to meaningful behavioral change remains po...
Advances in establishing real-time river water quality monitoring networks combined with novel artificial intelligence techniques for more accurate forecasting is at the forefront of urban water management. The preservation and improvement of the qua...
Wireless Capsule Endoscopy (WCE) is a procedure to examine the human digestive system for potential mucosal polyps, tumours, or bleedings using an encapsulated camera. This work focuses on polyp detection within WCE videos through Machine Learning. W...
Sequential linear models can be adopted to describe the data where the response variable depends on lagged outcomes and fixed-effects variables. For estimation, variable selection, and high-accuracy response prediction, we propose the penalized metho...
Model Predictive Control (MPC) has emerged as a promising approach for energy management in hybrid electric vehicles, enabling predictive optimization of powertrain operation. The energy management problem in parallel hybrid powertrains constitutes a...
Sequential recommendation systems face challenges in integrating local sequential patterns with global collaborative information. While Transformers capture long-term dependencies through self-attention, they suffer from quadratic complexity. State-s...
Using a sequential slack-based measure (SSBM) model, this paper analyzes the spatiotemporal disparities of urban land use economic efficiency (ULUEE) under environmental constraints, and its influencing factors in 270 cities across China from 2003–20...
Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain...
Barite is ubiquitous and known to incorporate 226Ra through the formation of a solid-solution. In U mining mill tailings, barite is one of the dominant sulfate-binding minerals. In such environments, sequential extractions are generally used to ident...
The problem with computer model calibration by tuning the parameters associated with computer models is significant in many engineering and scientific applications. Although several methods have been established to estimate the calibration parameters...
In recent years, the remarkable versatility of large language models (LLMs) has spurred considerable interest in leveraging their capabilities for recommendation systems. Critically, we argue that the intrinsic aptitude of LLMs for modeling sequentia...
The application of robots is growing in most countries, occupying a relevant place in everyday environments. Robots are still affected by errors due to their limitations, which may compromise the final performance. Accurate trajectories and positioni...
Honeycomb structure composites are taking an increasing proportion in aircraft manufacturing because of their high strength-to-weight ratio, good fatigue resistance, and low manufacturing cost. However, the hollow structure is very prone to liquid in...
Inundation forecast models with non-sequential regressors are advantageous in efficiency due to their rather fewer input variables required to be processed. This type of model is nevertheless rare mainly because of the difficulty in finding the prope...
The Uppsala model explains the traditional internationalisation process of multinational enterprises (MNEs), which gradually begin to internationalise from countries with smaller psychic distances. However, in the turbulent global economy, an increas...
Multi-behavior sequential recommendation (MBSRec) is a form of sequential recommendation. It leverages users’ historical interaction behavior types to better predict their next actions. This approach fits real-world scenarios better than tradit...
Sequential data prediction is a crucial area in healthcare. Healthcare data have the characteristics of non-stationarity, long-range dependence (LRD), and irregular sampling. Modeling these complex temporal features is highly challenging. Recurrent N...
As the e-commerce industry rapidly expands, the number of users and items continues to grow, making it increasingly difficult to capture users’ purchasing patterns. Sequential recommendation models have emerged to address this issue by predicti...
To address the damage and failure of electromechanical structures such as Printed Circuit Board (PCB) modules and battery assemblies under multiple impacts, this study combined experimental and modeling approaches to quantitatively investigate the in...
In the sequential three-way decision model (S3WD), conditional probability and decision threshold pair are two key elements affecting the classification results. The classical model calculates the conditional probability based on the strict equivalen...
The construction of a repository for geological disposal of radioactive waste will include the use of cement-based materials. Following closure, groundwater will saturate the repository and the extensive use of cement will result in the development o...
In spite of the increasing importance of corporate social responsibility (CSR) and employee job performance, little is still known about the links between the socially responsible actions of organizations and the job performance of their members. In...
The polysilicon production process has significant potential to be made adjustable, and actively changing its production schedule to participate in grid dispatch can effectively alleviate the pressure on the power supply and balance demand while prom...
Due to the complicated metabolism of mammalian cells, the corresponding dynamic mathematical models usually consist of large sets of differential and algebraic equations with a large number of parameters to be estimated. On the other hand, the measur...
As an effective method for uncertain knowledge discovery and decision-making, the three-way decisions model has attracted extensive attention from scholars. However, in practice, the existing sequential three-way decision model often faces challenges...
The construction of a repository for the geological disposal of radioactive waste will include the use of cement-based materials. Following closure, groundwater will saturate the repository, and the extensive use of cement will result in the developm...
To solve the timing uncertainty in low-voltage circuits, this paper proposes an analytical sequential path delay model based on the lognormal distribution. Unlike previous works that primarily focus on combinational logic, our model provides a comple...
The rapid evolution of online learning environments has generated diverse and complex data ecosystems. Recommender systems play a central role in leveraging such heterogeneous data to support personalised learning experiences. However, many deep lear...
The innovation of private enterprises plays a crucial role. This study focuses on the impacts of market information asymmetry, the technology spillover effect, and the order of innovation research and development (R&D) decisions on the evolution...
Background/Objectives: Chronic stress contributes to obesity through maladaptive eating behaviors, including emotional eating (eating due to negative emotions) and binge eating (consuming large amounts of food with a loss of control). A theoretical m...
Computational fluid dynamics (CFD)-driven optimization of engineering systems is often constrained by high computational cost, particularly when surrogate models must be constructed from limited simulation samples. Although surrogate-assisted multi-o...
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