Fog computing (FC) has been presented as a modern distributed technology that will overcome the different issues that Cloud computing faces and provide many services. It brings computation and data storage closer to data resources such as sensors, cameras, and mobile devices. The fog computing paradigm is instrumental in scenarios where low latency, real-time processing, and high bandwidth are critical, such as in smart cities, industrial IoT, and autonomous vehicles. However, the distributed nature of fog computing introduces complexities in managing and predicting the execution time of tasks across heterogeneous devices with varying computational capabilities. Neural network models have demonstrated exceptional capability in prediction tasks because of their capacity to extract insightful patterns from data. Neural networks can capture non-linear interactions and provide precise predictions in various fields by using numerous layers of linked nodes. In addition, choosing the right inputs is essential to forecasting the correct value since neural network models rely on the data fed into the network to make predictions. The scheduler may choose the appropriate resource and schedule for practical resource usage and decreased make-span based on the expected value. In this paper, we suggest a model Neural Network model for fog computing task time execution prediction and an input assessment of the Interpretive Structural Modeling (ISM) technique. The proposed model showed a 23.9% reduction in MRE compared to other methods in the state-of-arts.

The efficiencies and performance of gas turbine cycles are highly dependent on parameters such as the turbine inlet temperature (TIT), compressor inlet temperature (T1), and pressure ratio (Rc). This study analyzed the effects of these parameters on the energy efficiency, exergy efficiency, and specific fuel consumption (SFC) of a simple gas turbine cycle. The analysis found that increasing the TIT leads to higher efficiencies and lower SFC, while increasing the To or Rc results in lower efficiencies and higher SFC. For a TIT of 1400 ℃, T1 of 20 ℃, and Rc of 8, the energy and exergy efficiencies were 32.75% and 30.9%, respectively, with an SFC of 187.9 g/kWh. However, for a TIT of 900 ℃, T1 of 30 ℃, and Rc of 30, the energy and exergy efficiencies dropped to 13.18% and 12.44%, respectively, while the SFC increased to 570.3 g/kWh. The results show that there are optimal combinations of TIT, To, and Rc that maximize performance for a given application. Designers must consider trade-offs between efficiency, emissions, cost, and other factors to optimize gas turbine cycles. Overall, this study provides data and insights to improve the design and operation of simple gas turbine cycles.

Inequity in infrastructure distribution and social injustice’s effects on Ethiopia’s efforts to build a democratic society are examined in this essay. By ensuring fair access to infrastructure, justice, and economic opportunity, those who strive for social justice aim to redistribute resources in order to increase the well-being of individuals, communities, and the nine regional states. The effects that social inequity and injustice of access to infrastructure have on Ethiopia’s efforts to develop a democratic society were the focus of the study. Time series analysis using principal component analysis (PCA) and composite infrastructure index (CII), as well as structural equation modeling–partial least squares (SEM-PLS), were necessary to investigate this issue scientifically. This study also used in-depth interviews and focus group discussions to support the quantitative approach. The research study finds that public infrastructure investments have failed or have been disrupted, negatively impacting state- and nation-building processes of Ethiopia. The findings of this research also offer theories of coordination, equity, and infrastructure equity that would enable equitable infrastructure access as a just and significant component of nation-building processes using democratic federalism. Furthermore, this contributes to both knowledge and methodology. As a result, indigenous state capability is required to assure infrastructure equity and social justice, as well as to implement the state-nation nested set of policies that should almost always be a precondition for effective state- and nation-building processes across Ethiopia’s regional states.

Introduction: Many detrimental effects on employees’ health and wellbeing might result from inadequate illumination in the workplace. Headaches and trouble focusing can result from eye strain brought on by inadequate illumination. The purpose of this study was to simulate and optimize workplace illumination in the ceramic industry. Materials and methods: A common Luxmeter ST-1300 was used to measure the illumination in seven workplaces at a height of 100 cm above the floor. DIALux evo version 7.1 software was used to simulate the illumination of workplaces. To optimize the illumination conditions, a numerical experiment design consisting of 16 scenarios was used for each of the workplaces. Four factors were considered for each scenario: luminaire height, number of luminaires, luminous flux, and light loss factor. The Design-Expert program version 13.0.5.0 was applied for developing the scenarios. Finally, by developing quadratic models for each workplace, the optimization process was implemented. Results: Every workplace had illumination levels that were measured to be between 250 and 300 lux. Instead of using compact fluorescent luminaires, LED technology was recommended to maximize the illumination conditions for the workers. Following optimization, 376 lux of illumination were visible at each workstation in every workspace. For the majority of the workspaces, the simulated illumination was expected to have a desirability degree greater than 0.9. The uniformity and illumination of the workplace were significantly impacted by the two factors of luminaire height and luminaire count. Conclusion: The primary outcomes of this optimization were the environmental, political, and socioeconomic ones, including reduced consumption power, high light flux, and environmental compatibility. Nonetheless, the optimization technique applied in this work can be applied to the design of similar situations, such as residential infrastructure.