Heating, ventilation, and air-conditioning systems (HVAC) have significant potential to support demand response programs within power grids. Model Predictive Control (MPC) is an effective technique for utilizing the flexibility of HVAC systems to ach...
The aim of this study was to create a radiomics model for Locally Advanced Cervical Cancer (LACC) patients to predict pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NACRT) analysing T2-weighted 1.5 T magnetic resonance imag...
In this study, the effects of reduction temperature and time on the reduction rates of iron and vanadium oxides in low-grade vanadium–titanium magnetite (VTM) were investigated. Based on the results of physical experiments, both the response su...
16 January 2023
Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram mode...
In today’s data-driven marketing landscape, predicting customer responses to marketing campaigns is essential for optimizing both engagement and Return On Investment (ROI). This study aims to develop a predictive model using a Decision Tree (DT...
Background/Objective: Predicting pharmacological response in cancer remains a key challenge in precision oncology due to intertumoral heterogeneity and the complexity of drug–gene interactions. While machine learning models using multi-omics da...
There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected con...
Pretreatment response prediction is crucial to select those patients with rectal cancer who will benefit from organ preservation strategies following (intensified) neoadjuvant therapy and to avoid unnecessary toxicity in those who will not. The combi...
Introduction: A major challenge in Romania is the optimisation of antiretroviral therapy for the many HIV-infected adults with, on average, a decade of treatment experience. The RDI has developed computational models that predict virological response...
The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predicti...
The equilibrium swelling test was employed to determine the swelling response of Nitrile Butadiene Rubber (NBR) with various acrylonitrile (ACN) contents, and the three-dimensional solubility parameter (HSP) and modified Flory–Huggins interacti...
Recently, the integration of optimal battery dispatch and demand response has received much attention in improving DC microgrid operation under uncertainties in the grid-connect condition and distributed generations. However, the majority of prior st...
This paper focuses on flexible friction dampers (or “strips”) mounted on the underside of adjacent turbine blade platforms for sealing and damping purposes. A key parameter to ensure a robust and trustworthy design is the correct prediction of the ma...
This paper proposes an innovative algorithm for forecasting the motion response of floating offshore wind turbines by employing force-to-motion transfer functions and state-space models. Traditional numerical integration techniques, such as the Newma...
The need to maintain the highest possible levels of bioactive components contained in raw materials requires the elaboration of tools supporting their processing operations, starting from the first stages of the food production chain. In this study,...
The growing demand for electricity is a challenge for the electricity sector as it not only involves the search for new sources of energy, but also the increase of generation capacity of the existing electrical infrastructure and the need to upgrade...
This paper proposes a novel approach that unifies a demand response (DR) with a master plan of the model predictive control method focusing on scheduling maintenance and replacement for suboptimal equipment in real-time solar power plants. By leverag...
Response surface models (RSMs) are a new trend in modern anesthesia. RSMs have demonstrated significant applicability in the field of anesthesia. However, the comparative analysis between RSMs and logistic regression (LR) in different surgeries remai...
Jack-up offshore platforms are widely used in many fields, and it is of great importance to quickly and accurately predict the dynamic response of platform pile leg structures in real time. The current analytical techniques are founded upon numerical...
Pavement icing imposes a great threat to driving safety and impacts the efficiency of the road transportation system in cold regions. This has attracted research predicting pavement icing time to solve the problems brought about by icing. Different m...
In this paper, the response surface methodology (RSM) is used to predict the flashover voltage of a cap and pin 1512L insulator used by SONELGAZ Algerian Power Company (SPE). The pollution and conductivity are studied using a two-level central compos...
30 December 2016
To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers’ perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision info...
By using omics, we can now examine all components of biological systems simultaneously. Deep learning-based drug prediction methods have shown promise by integrating cancer-related multi-omics data. However, the complex interaction between genes pose...
Metal-oxide (MOX) gas sensors are widely used for gas concentration estimation and gas identification due to their low cost, high sensitivity, and stability. However, MOX sensors have low selectivity to different gases, which leads to the problem of...
In this paper, eight variables of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate and flow are used as network input and slump is used as network output to construct a back-propagation (BP) neural networ...
This work aims at underscoring the need for the accurate quantification of the sensitivities (i.e., functional derivatives) of the results (a.k.a. “responses”) produced by large-scale computational models with respect to the models’ parameters, which...
Currently, machine learning techniques are widely used in structural seismic response studies. The developed network models for various types of seismic response provide new ways to analyse seismic hazards. However, it is not easy to balance the appl...
Numerical models, such as multibody dynamics ones, are broadly used in various engineering applications, either as an integral part of the preliminary design of a product or simply to analyze its behavior. Aiming to increase the accuracy and potentia...
Rock’s response time to blasting (Tmin) refers to the critical time elapsed between the detonation of the explosive to the fragmentation and displacement of the rock, and it is a fundamental parameter that directly impacts blast-induced fragmen...
Deep neural networks (DNNs) have gained prominence in addressing regression problems, offering versatile architectural designs that cater to various applications. In the field of earthquake engineering, seismic response prediction is a critical area...
Objective: Our objective was to develop a radiomics model based on magnetic resonance imaging (MRI) and contrast-enhanced computed tomography (CE-CT) to predict pathological complete response (pCR) to neoadjuvant treatment in locally advanced rectal...
Surface wear, as a major failure mode of gear systems, is an unavoidable phenomenon during the whole life of gears. It also induces other gear damages, such as fatigue cracks, surface pitting and spalling. Ultimately, those defects may result in the...
Background: Cancer cell lines are frequently used in research as in-vitro tumor models. Genomic data and large-scale drug screening have accelerated the right drug selection for cancer patients. Accuracy in drug response prediction is crucial for suc...
Coastal zones are facing intensive ecological pressures and challenges, which could vary over a wide range of spatiotemporal scales. Our limited capability to understand and especially predict this variability can lead to the misinterpretation of coa...
To address the stochastic, nonlinear, and strongly coupled characteristics of multivariate long-term structural response in bridge health monitoring, this study proposes the Informer-SEnet prediction model. The model integrates a Squeeze-and-Excitati...
Purpose: Early treatment response assessments are crucial, and the results are known to better correlate with prognosis and survival outcomes. The present study was conducted to differentiate true progression (TP) from pseudoprogression (PsP) in long...
This work was conducted in order to validate a pre-treatment quantitative ultrasound (QUS) and texture derivative analyses-based prediction model proposed in our previous study to identify responders and non-responders to neoadjuvant chemotherapy in...
Changium smyrnioides, an endangered herb known for its medicinal roots, contains essential amino acids that are vital for human health but cannot be synthesized by the body. However, wild populations of this species have been steadily declining due t...
This study presents a model of starved mixed Elastohydrodynamic Lubrication (EHL) in point and line contact to investigate the lubrication performance and material response. In formulating the governing equations for the lubrication, the dimensional...
Colorectal cancer is the third most common cancer in the world, with an annual incidence of 2 million cases. The success of first-line chemotherapy plays a crucial role in determining the disease outcome. Therefore, there is an increasing demand for...
The proposed study presents a novel probabilistic method for optimal allocation of spinning reserves taking into consideration load, wind and solar forecast errors, inter-zonal spinning reserve trading, and demand response provided by consumers as a...
This work presents a perspective on deterministic predictive modeling methodologies, which aim at extracting best-estimate values for model responses and parameters along with reduced predicted uncertainties for these best-estimate values. The two ol...
The integration of a high proportion of renewable energy has significantly reduced the grid inertia level and markedly increased the risk of transient frequency instability in power systems. Meanwhile, the large-scale integration of diverse heterogen...
A Machine Learning (ML)-based surrogate modeling framework is presented for mapping structure–property relationships in architected Ti6Al4V cylindrical TPMS metamaterials subjected to quasi-static compression. A Python–nTop pipeline autom...
Background: Assessing the efficacy of combination therapies in hepatocellular carcinoma (HCC) requires both accurate tumor delineation and biologically validated prediction of therapeutic response. Conventional MRI-based criteria, which rely primaril...
Background: This study aimed to develop a model that automatically predicts the neoadjuvant chemoradiotherapy (nCRT) response for patients with locally advanced cervical cancer (LACC) based on T2-weighted MR images and clinical parameters. Methods: A...
To comprehensively obtain the effect of the machining process on the three-dimensional surface topography of machined potassium dihydrogen phosphate crystals, a dynamic response model of a machining system was built to calculate the dynamic displacem...
Background: Disease-modifying antirheumatic drugs (bDMARDs) have shown efficacy in treating Rheumatoid Arthritis (RA). Predicting treatment outcomes for RA is crucial as approximately 30% of patients do not respond to bDMARDs and only half achieve a...
We investigate the association of a sensitive characteristic or latent variable with observed binary random variables by the randomized response (RR) technique of Warner in his publication (Warner, S.L. J. Am. Stat. Assoc.1965, 60, 63–69) and a...
Head and neck squamous cell carcinoma (HNSCC) is characterized by a poor 5 year survival and varying response rates to both standard-of-care and new treatments. Despite advances in medicine and treatment methods, mortality rates have hardly decreased...
of 247