21.4.5.2. Non-Iterative Time-Advancement Scheme The iterative time-advancement scheme requires a considerable amount of computational effort due to a large number of outer iterations performed for each time-step. The idea underlying the non-iterative time-advancement (NITA) scheme is that, in order...
The initial temperature value within the PCM-filled domain was 25 °C. The Non-Iterative time advancement (NITA) scheme was operated, as this scheme was proved to save >90 % of numerical modelling time with error value lower than (0.28 %) as stated by Ezzat et al. [54]. The PISO alg...
As opposed to the iterative time advancement (ITA), which requires a considerable number of outer iterations, the use of the NITA scheme significantly reduces the computational time [27], [36]. Time discretisation is second-order implicit. Two time steps are used: Δt1 = 8 × 10−4 s ...
Iterative prototype construction and assembly have not been taken into account commonly in the planning of assembly ergonomics. This article presents DFMA queries considering factors in geometry and construction that affect the adjustability and adaptability during prototype construction. The example case ...
Iterative multi‑scale dynamic time warping. The algorithms we proposed in this paper to estimate heart rate from the video camera data, required the PPGi signal to be regular for short-time periods of a typical duration between 15 and 30 s (see Fig. 8e). This is required so ...
[85] suggest that firms seeking assurance are more likely to revise and improve their disclosures over time. This iterative process, where firms issue restatements to correct errors or omissions, reflects a commitment to transparency and continuous improvement in reporting quality. The application of ...
The fast advancement of scRNA-seq technology has led to the discovery of an increasing amount of important single-cell data, which is very helpful for our understanding of single-cell but also presents several obstacles. In single-cell data, there are many noises and outliers, which pose challe...
We propose an efficient non-iterative topology optimization pipeline using deep learning for heat conduction structure design. Our pipeline contains two main steps: (1) near-optimal structure prediction in coarse resolution, and (2) structure refinement to obtain final structure in fine resolution. Bot...
CARNA generated a dot-plot of probabilities of basepairing which was used to generate a consensus sequence and structure, used in an iterative manner to optimize an alignment based on secondary structure conservation. This alignment was very slightly modified by hand to allow a couple additional ...
REF is iterative, which means it takes into account how the removal of one feature affects the importance of others. This makes the method adaptive and potentially more robust, useful for radiomics where the interactions between features can be complex [39]. Boruta: This is a randomized feature...