Search results for "PREDICT"
showing 10 items of 2174 documents
A comprehensive analysis of Universal Soil Loss Equation-based models at the Sparacia experimental area
2020
Improving Universal Soil Loss Equation (USLE)‐based models has large interest because simple and reliable analytical tools are necessary in the perspective of a sustainable land management. At first, in this paper, a general definition of the event rainfall‐ runoff erosivity factor for the USLE‐based models, REFₑ = (QR)ᵇ¹(EI₃₀)ᵇ², in which QR is the event runoff coefficient, EI₃₀ is the single‐storm erosion index, and b₁ and b₂ are coefficients, was introduced. The rainfall‐runoff erosivity factors of the USLE (b₁ = 0 and b₂ = 1), USLE‐M (b₁ = b₂ = 1), USLE‐MB (b₁ ≠ 1 and b₂ = 1), USLE‐MR (b₁ = 1 and b₂ ≠ 1), USLE‐MM (b₁ = b₂ ≠ 1), and USLE‐M2 (b₁ ≠ b₂ ≠ 1) can be defined using REFₑ. Then t…
A combination of umbilical artery PI and normalized blood flow volume in the umbilical vein: Venous–arterial index for the prediction of fetal outcome
2008
Abstract Objective The objective was to assess the diagnostic power of the umbilical venous–arterial index (VAI) as a combination of the pulsatility index in the umbilical artery and the normalized blood flow volume in the umbilical vein for the prediction of poor fetal outcome. Study design This was a prospective clinical study in which the umbilical artery PI (UAPI), the normalized umbilical vein blood volume flow rate ( n UV; ml/min/kg estimated fetal body weight), the venous–arterial index (VAI; n UV/UAPI), and the pulsatility index (PI) in the umbilical artery (UA), uterine artery (utA), middle cerebral artery (MCA), and aorta were determined in 181 fetuses once (at between 17 and 41 w…
Micromechanisms of load transfer in a unidirectional carbon fibre-reinforced epoxy composite due to fibre failures: Part 3. Multiscale reconstruction…
2008
International audience; This third article describes a multiscale process which takes into account the most important microscopic phenomena associated with composite degradation, including fibre fractures and interfacial debonding, overloading of fibres neighbouring a fibre break as well as viscoelastic behaviour of the matrix. The results have been used to accurately predict the macroscopic failure of unidirectional carbon fibre-reinforced epoxy and quantify damage accumulation in pressure vessels made of the same material. The approach described has allowed the acoustic emission activity resulting from fibres breaks to be evaluated and shown how the residual lifetimes of such vessels, whe…
Analysis of the unpredictable migration of impacted mandibular third molars: A pilot study
2020
Background Eruption of an impacted mandibular third molar (3MM) is often unpredictable. The objective of this study was to establish the radiographic parameters of migration in patients whose 3MMs evolved unpredictably. Material and Methods This was a retrospective observational study. Patients with unusual 3MM migration (away from their physiological eruption position with changes in the longitudinal and horizontal axes) and with at least two panoramic radiographs were included. To evaluate the radiographic parameters, images were superimposed, using mandibular angle and ipsilateral condyle as references. Results Of a total of 2851 patients, four were included in our study. The average age…
Continuous Discharge Monitoring Using Non-contact Methods for Velocity Measurements: Uncertainty Analysis
2014
At gauged site, water stage and discharge hydrographs can be related also during unsteady flow conditions, using the one-dimensional diffusive hydraulic model, DORA, and exploiting sporadic surface velocity measurements carried out with a radar sensor, during the rising limb of the flood. Indeed, starting from the measured surface velocity, the application of a simplified entropic velocity distribution model allows obtaining the benchmark discharge for the Manning’s roughness calibration. The aim of this work is twofold. First, to address the uncertainty of the approach. Second, to detect the minimum water level along the rising limb in which the occasional surface velocity measurement shou…
The Role of Novel Bladder Cancer Diagnostic and Surveillance Biomarkers—What Should a Urologist Really Know?
2022
The aim of this review is to analyze and describe the current landscape of bladder cancer diagnostic and surveillance biomarkers. We researched the literature from 2016 to November 2021 to find the most promising new molecules and divided them into seven different subgroups based on their function and location in the cell. Although cystoscopy and cytology are still the gold standard for diagnosis and surveillance when it comes to bladder cancer (BCa), their cost is quite a burden for national health systems worldwide. Currently, the research is focused on finding a biomarker that has high negative predictive value (NPV) and can exclude with a certainty the presence of the tumor, considering…
Infrequent promoter methylation of the MGMT gene in liver metastases from uveal melanoma.
2008
Uveal melanoma is associated with a high mortality rate once metastases occur, with over >90% of metastatic patients dying within less than 1 year from metastases to the liver. The intraarterial hepatic (iah) administration of the alkylating agent fotemustine holds some promise with response rates of 36% and median survival of 15 months. Here, we investigated whether the DNA-repair-protein MGMT may be involved in the variability of response to fotemustine and temozolomide in uveal melanoma. Epigenetic inactivation of MGMT has been demonstrated to be a predictive marker for benefit from alkylating agent therapy in glioblastoma. We found a methylated MGMT promoter in 6% of liver metastases fr…
Signal Spectrum-Based Machine Learning Approach for Fault Prediction and Maintenance of Electrical Machines
2022
Industrial revolution 4.0 has enabled the advent of new technological advancements, including the introduction of information technology with physical devices. The implementation of information technology in industrial applications has helped streamline industrial processes and make them more cost-efficient. This combination of information technology and physical devices gave birth to smart devices, which opened up a new research area known as the Internet of Things (IoT). This has enabled researchers to help reduce downtime and maintenance costs by applying condition monitoring on electrical machines utilizing machine learning algorithms. Although the industry is trying to move from schedu…
Digital Twin framework for automated fault source detection and prediction for comfort performance evaluation of existing non-residential Norwegian b…
2023
Numerous buildings fall short of expectations regarding occupant satisfaction, sustainability, or energy efficiency. In this paper, the performance of buildings in terms of occupant comfort is evaluated using a probabilistic model based on Bayesian networks (BNs). The BN model is founded on an in-depth anal- ysis of satisfaction survey responses and a thorough study of building performance parameters. This study also presents a user-friendly visualization compatible with BIM to simplify data collecting in two case studies from Norway with data from 2019 to 2022. This paper proposes a novel Digital Twin approach for incorporating building information modeling (BIM) with real-time sensor data…
Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys
2022
Fatigue cracks are a major defect in metal alloys, and specifically, their study poses defect evaluation challenges in aluminum aircraft alloys. Existing inline inspection tools exhibit measurement uncertainties. The physical-based methods for crack growth prediction utilize stress analysis models and the crack growth model governed by Paris’ law. These models, when utilized for long-term crack growth prediction, yield sub-optimum solutions and pose several technical limitations to the prediction problems. The metaheuristic optimization algorithms in this study have been conducted in accordance with neural networks to accurately forecast the crack growth rates in aluminum alloys. Through ex…