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An accurate medium-term streamflow forecast is one of the significant functions for managing and planning water resources. Considering the characteristics of trend, periodicity, and stochasticity of streamflow into account. So, this research aims to develop a new strategy, including a singular spectrum analysis (SSA) technique and a linear autoregressive (AR) model to predict monthly Tigris River streamflow data with three scenarios. The first scenario applies the SSA to decompose the normalised and cleaned time series into different signals (i.e., trend, seasonal, stochastic, and noise), then reconstruct the signals without noise and use the AR model to simulate the new time series. The second scenario employs the AR model to forecast each signal of streamflow without noise separately. The simulated time series was obtained by summing each predicted signal. The third scenario uses the AR model to simulate the raw data. Based on several statistical tests, the comparative analysis reveals that the first and second scenarios were much more accurate than the third ones. The second scenario is the best, reaching RMSE = 0.1223 (m3/s) and MAE = 0.0913 (m3/s) in the testing phase. The novelty of this study lies in the comparative evaluation of three SSA-AR modelling scenarios and the finding that forecasting decomposed components individually leads to superior accuracy compared to conventional approaches. The results are of substantial significance to the Ministry of Water Resources in managing and planning freshwater resources amid growing water demand.
Tilted solar stills are a promising option for sustainable water desalination, but their productivity is limited by low evaporation and condensation efficiencies. This study presents a dual-functional strategy for improving the performance of a modified tilted solar still using a mesh cotton wick to enhance water distribution and continuous surface wetting and a thermoelectric cooling tube to lower the condensing surface temperature and increase the condensation rate, thus increasing the overall system productivity. Tests were conducted in Yekaterinburg, Russia, under identical environmental conditions for both the modified tilted solar still and the conventional still. The results demonstrated a significant improvement in the modified system, with a 40% increase in freshwater production. The maximum daily production was 1.290 L/m2 from the cooling channel and 0.615 L/m2 from the glass cover, compared to 0.805 and 0.555 L/m2 for the conventional system. Thermal efficiency reached 13% versus 9% for the conventional system. Economic analysis confirmed the system's viability, with the cost of distilled water reduced to $0.0296/L, 13.7% lower than the conventional system, while maintaining competitive costs at varying utility rates. These results demonstrate the effectiveness of the wick-thermoelectric cooling integrated approach in providing a low-cost, energy-efficient, scalable solar desalination solution suitable for arid and energy-limited regions. This study presents a two-part strategy for increase the productivity of a modified tilted solar still: a mesh cotton wick to enhance water distribution and continuous surface wetting and; a thermoelectric cooling tube to lower the condensing surface temperature and increase the condensation rate.
This study presents a numerical investigation focused on optimizing natural convection heat transfer (HT) inside a circular cavity that features alternating heated, cooled, and insulated wall segments. The analysis addresses configurations both with and without a centrally inserted cold cylinder. The research involves two-dimensional, steady, laminar flow of incompressible fluids, such as air (Pr = 0.71) and water (Pr = 7.1), and variation of Rayleigh numbers (Ra) ranging from 10 & sup3; to 10(5) solved using the finite element method (FEM) in COMSOL Multiphysics. Key parameters such as the average Nusselt number (Nu(avg)), entropy generation due to fluid friction (E-ff), entropy generation due to heat transfer (E-HT), total entropy generation (E-gen), and Bejan number (Be) were computed to evaluate the thermal and thermodynamic performance of the system. The results indicate that Ra plays a significant role in governing convective strength and HT, while Pr has a relatively minor impact on flow structure. The introduction of a cold inner cylinder enhances fluid mixing and thermal circulation, leading to Nu(avg) increases of 23%, 25%, and 44% for Ra values of 10 & sup3;, 10(4), and 10(5), respectively. While the total E-gen increased by only 0.5% to 4% due to higher frictional irreversibility, the overall thermal performance showed significant improvement. Moreover, the increase in Nu(avg) using the internal cylinder can compensate for the adverse effect of the cylinder on the hydraulic performance. Response surface methodology (RSM) confirmed the strong correlation of Nu(avg) and E-gen with Ra and the cylinder radius (r), demonstrating excellent model reliability with R & sup2; > 0.99. The proposed configuration offers practical potential for thermal optimization in lab-on-chip devices, microreactors, and energy-efficient thermal control applications.
With the proliferation of smartphones and other mobile devices, there has been a significant increase in mobile data consumption. To cope with the high load in the access part of cellular networks, network operators employ various strategies. Data offloading is indeed a promising solution for alleviating network congestion and improving data transmission in cellular networks. It involves diverting data traffic from cellular networks to other available wireless technologies, such as Wi-Fi or femtocells, that can provide additional bandwidth and capacity. By addressing performance issues and considering cost aspects through proper deployment, configuration, and management of access points (APs), Wi-Fi-based offloading can be optimized to provide efficient data transmission, alleviate cellular network congestion, and enhance the overall user experience. In this paper, a multi-objective problem is proposed to find the best locations of Wi-Fi APs providing the optimum performance of offloading in terms of throughput and offloaded traffic. Three optimization algorithms are applied to solve the problem include Genetic Algorithm (GA), Krill Herd Algorithm (KHA) and Sine Cosine Algorithm (SCA). The main contribution of this paper is to investigate the capabilities of every optimization method in providing the maximum performance metrics in single or multiple forms for data offloading. The evaluation results indicate that the SCA can provide the best performance in all scenarios due to its solution approach of black box model. The KHA provides more performance improvement than the GA method due to its approach of local optima finding using the exploitation phase. The superiority of GA method is its high convergence speed due to mutation in each iteration.
The main purpose of this work is to propose a nonlinear non-Markovian model of subdiffusive transportation that involves chemotactic substance affecting the cells' movement. In this case, both of the random waiting time and the escape rate are affected by a chemotactic gradient. We systematically derive the subdiffusive fractional master equation, then we consider the diffusive limit of the fractional master equation. Finally, a Monte-Carlo simulation is run for the model in order to analyse the role of the chemotactic gradient in the diffusion of particles.
