Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.
The dynamic behavior of a body-in-white (BIW) structure has significant influence on the noise, vibration, and harshness (NVH) and crashworthiness of a car. Therefore, by improving the dynamic characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural optimization subjected to dynamic load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process.
Over the last few years, particle swarm optimization (PSO) has been extensively applied in various geotechnical engineering including slope stability analysis. However, this contribution was limited to two-dimensional (2D) slope stability analysis. This paper applied PSO in three-dimensional (3D) slope stability problem to determine the critical slip surface (CSS) of soil slopes. A detailed description of adopted PSO was presented to provide a good basis for more contribution of this technique to the field of 3D slope stability problems. A general rotating ellipsoid shape was introduced as the specific particle for 3D slope stability analysis. A detailed sensitivity analysis was designed and performed to find the optimum values of parameters of PSO. Example problems were used to evaluate the applicability of PSO in determining the CSS of 3D slopes. The first example presented a comparison between the results of PSO and PLAXI-3D finite element software and the second example compared the ability of PSO to determine the CSS of 3D slopes with other optimization methods from the literature. The results demonstrated the efficiency and effectiveness of PSO in determining the CSS of 3D soil slopes.
Peat fires in tropical peatland release a substantial amount of carbon into the environment and cause significant harm to peatlands and the ecology, resulting in climate change, biodiversity loss, and the alteration of the ecosystem. It is essential to understand peat fires and to develop more effective methods for controlling them. To estimate carbon emissions and monitor fires, the depth of burning can measure the overall burnt down the volume, which is proportional to the carbon emissions that are emitted to the environment. The first step is to understand the technique of measuring the depth of the burn. However, there is a lack of integrated information regarding the burning depth for peat fires. This review paper discusses the techniques used to measure the burning depth, with particular attention given to quantifying carbon emissions. The article also provides information on the types of methods used to determine the burning depths. This research contributes to the field of peat fire by providing a readily available reference for practitioners and researchers on the current state of knowledge on peat fire monitoring systems.
Microbiologically influenced corrosion (MIC) is among the common corrosion types for buried and deep-water pipelines that result in costly repair and pipeline failure. Sulfate-reducing bacteria (SRB) are commonly known as the culprit of MIC. The aim of this work is to investigate the performance of combination of ultrasound (US) irradiation and ultraviolet (UV) radiation (known as Hybrid soliwave technique, HyST) at pilot scale to inactivate SRB. The influence of different reaction times with respect to US irradiation and UV radiation and synergistic effect toward SRB consortium was tested and discussed. In this research, the effect of HyST treatment toward SRB extermination and corrosion studies of carbon steel coupon upon SRB activity before and after the treatment were performed using weight loss method. The carbon steel coupons immersed in SRB sample were exposed to HyST treatment at different time of exposure. Additionally, Field Emission Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy were used to investigate the corrosion morphology in verifying the end product of SRB activity and corrosion formation after treatment. Results have shown that the US irradiation treatment gives a synergistic effect when combined with UV radiation in mitigating the SRB consortium.
Proposals have been made by several researchers to conduct the sequestration of carbon dioxide (CO2) through calcium and magnesium-rich materials. From these materials, ground granulated blast furnace slag (GGBS) containing 5% magnesium and 45% calcium is seen to be a good candidate and is available to sequester CO2. This study intends to ascertain the ability to absorb CO2, sequester it, and increase treated kaolin strength with different content of GGBS under various carbonation periods with varying CO2 pressure. The impacts of carbonated GGBS on the mechanical attributes of soil were examined by conducting the unconfined compressive strength (UCS) test, and microstructure analysis was conducted to identify the changes in the structure and Crestline phase. Stationary carbonation in a triaxial test with pure CO2 was conducted to accelerate the carbonation process. The outcome indicates that the strength rises as the carbonation period rises. Likewise, UCS rises as the CO2 pressure rises from 100 to 200 kPa. It could be concluded that augmentation of the strength is because of carbonated calcium and magnesium products which stuff the soil voids. Changes occur on the microstructure level due to carbonation as well.
Environmental global issues affecting global warming, such as carbon dioxide (CO2), have attracted the attention of researchers around the world. This paper reviews and discusses the ground improvement and its contribution to reducing CO2 in the atmosphere. The approach is divided into three parts: the Streamlined Energy and Emissions Assessment Model (SEEAM), the replacement of soil stabilisation materials that lead to the emission of a large amount of CO2 with alternatives and mineral carbonation. A brief discussion about the first two is reviewed in this paper and a detailed discussion about mineral carbonation and its role in enhancing soil strength while absorbing a large amount of CO2. It is emphasised that natural mineral carbonation requires a very long time for a material to reach its full capacity to form CO2; as a result, different acceleration processes can be done from increasing pressure, temperature, the concentration of CO2 and the addition of various additives. In conclusion, it was found that magnesium is more attractive than calcium, and calcium is complicated in terms of strength behaviour. Magnesium has a larger capacity for CO2 sequestration and it has a greater potential to increase soil strength than calcium.