Synthetic paraffinic kerosene (SPK) is an ultra-clean fuel with low aromatic content and negligible quantities of sulfur compounds. Although, SPK has a good potential to replace the conventional fuel Jet A-1, it also ...
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Synthetic paraffinic kerosene (SPK) is an ultra-clean fuel with low aromatic content and negligible quantities of sulfur compounds. Although, SPK has a good potential to replace the conventional fuel Jet A-1, it also has some deficiencies. One of them is the low lubricity compared to its conventional counterpart Jet A-1. To improve the lubricity of SPK, three selected additives have been mixed with SPK at different concentrations. The lubricity of the samples was determined experimentally and the samples that meet the industry specifications have been studied further. The effect of the additives on the physicochemical properties, such as, density, flash point, freezing point, viscosity, and heat content, were investigated. Linoleic acid was found to be an excellent lubricity improver even at a very low concentration and its negative impact on the other physicochemical properties was found to be insignificant. Ethyl oleate also demonstrated significant improvement in lubricity at low concentrations but had a negative impact on the fuel’s freezing point at high concentrations. Quinoline, at high concentrations, elevated the blend’s freezing point above the acceptable limits. In parallel to the experimental campaign, a pre-existing mathematical modelling tool was utilized to predict the properties of interest. The lubricity model was successfully introduced into the mathematical model in order to improve the capabilities of the model. Linoleic acid sample showed the best improvement in lubricity of SPK with wear scar diameter of 417 μm; well below the ASTM D7566 maximum limit of 850 μm. The dual nature of this study facilitated the optimization of the physicochemical properties of the fuel samples.
The article presents the findings of the study of the Georgievskoe deposit of geothermal waters. The methodology for estimating the energy potential of a water-bearing horizon (an aquifer) is demonstrated. The interre...
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Due to declining fertility rate and increasing life expectancy, population aging has become a growing problem in Hong Kong. Domestic elderly service providers and public health institutions have been suffering from a ...
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Due to declining fertility rate and increasing life expectancy, population aging has become a growing problem in Hong Kong. Domestic elderly service providers and public health institutions have been suffering from a shortage of experienced staff for elderly healthcare, which has led to a drop in both the quality and efficiency of the local elderly service. With the rising popularity of mobile applications and the betterment of machine vision technology, this paper describes the design of an Intelligent m-Healthcare System (ImHS) for relieving the manpower pressure on local elderly service providers by lowering the technical threshold and simplifying staff training process. Face recognition technology is applied to identify the elderly by searching and tracing the elderly medical record through the FaceAPI service. In addition, the proposed ImHS provides the immediate insight into healthcare knowledge for users, which lowers the occurrence of Adverse Drug Event (ADE) and shortens the duration of pill distribution process. By conducting a case study in a local elderly home, the proposed system allowed the nursing staff to better allocate healthcare resources and to improve the operation effectiveness and efficiency.
Universities and colleges have a constant focus on improving student retention and degree completion rates. Degree completion impacts the reputation of the institution, as it is a reflection of institutional ability t...
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Universities and colleges have a constant focus on improving student retention and degree completion rates. Degree completion impacts the reputation of the institution, as it is a reflection of institutional ability to prepare graduates with the specific skills that contribute to society through STEM majors. Colleges and universities collect considerable amounts of student data; however, efforts need to be made to utilize the data to increase student success. For instance, by determining the factors that influence student retention and completion rates, it is possible to improve advising through intentional student advising. To this end, this research presents the application of support vector machines (SVM) to predict degree completion within three years by STEM community college students. SVM enables the classification of the input variables into expected classes, completion and not completion, by maximizing the margin between the points from the different classes constraining the misclassification. The model was developed using data on 282 students with 9 variables. The variables included age, gender, degree, and college GPA, among others. The model results, which include prediction and variables ranking, offer an important understanding about how to develop a more efficient and responsive system to support students.
The healthy and sustainable development of irrigation area not only serves as the guarantee of national food production security, but also shoulders the important task of regional ecological security. However, the unr...
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The healthy and sustainable development of irrigation area not only serves as the guarantee of national food production security, but also shoulders the important task of regional ecological security. However, the unreasonable exploitation and utilization of water resources for a long time in the irrigation area has led to the coexistence of water shortage and waste as well as a series of ecological and environmental problems, restricting the benign development of the irrigation area. The groundwater level plays an important role in maintaining the regional ecological system. It is of great significance for the healthy development of the irrigation area to realize the rational utilization of the limited water resources by strictly implementing restriction of total water use on the basis of ensuring the reasonable groundwater level. Therefore, this study established a spatial-temporal optimal regulation method of water resources in the irrigation area by using the optimal allocation of water resources, coupling groundwater numerical technology and the characteristics of hydrological cycle with comprehensively consideration of the dual constraints between total water consumption and reasonable groundwater depth. Besides, taking Helan County, a typical area of Qingtongxia Irrigation district in Ningxia as an example, a case study on optimal allocation of irrigation water resources was carried out. The results show that the irrigation water demand in Helan County Irrigation District (HCID) decreases by considering the absorption of shallow groundwater by roots, and the corresponding water use spatial-temporal distribution is optimized under the combined action of total available water allocation and groundwater depths. Compared with the situation without considering the direct utilization of groundwater by roots, the irrigation water demand of HCID decreases by 5.625 million m 3 and 0.98%. Compared with the actual current water use situation, spatially, the variance of
Our world is now connected and even entangled in unprecedented ways through networked technologies. Yet pockets of unequal connectivity persist, and technical infrastructures for connectivity remain difficult to desig...
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In the current study, thermal patterns and flow resistance in a heat exchange tube equipped with a curved-wing tape (CWT) vortex generator were experimentally analyzed to boost performance. A range of Reynolds numbers...
In the current study, thermal patterns and flow resistance in a heat exchange tube equipped with a curved-wing tape (CWT) vortex generator were experimentally analyzed to boost performance. A range of Reynolds numbers (Re) from 4130 to 25,370 was utilized in the experiment. The curved wings were arranged in forward array patterns for pitch length ratios (P/D = PR = 2.5, 2, and 1.5) and three wing attack angles (α = 10°, 20°, and 30°). The friction factor, f, and the Nusselt number, Nu, were utilized to quantify the pressure loss and heat transmission caused by the CWT insertion. The measured data reveal that utilizing the CWT resulted in a roughly 2.55-4.37 times greater increase in Nu than the smooth tube, whereas the rise in f is approximately 7.36-46.9 times. Raising the α value causes the Nu and f to trend upward, but increasing PR causes them to trend downward. The CWT’s maximal thermal performance is approximately 1.58 at α = 10° and PR = 1.5. Correlations for f and Nu in the functional form of the CWT parameters have also been established.
Currently, deep learning algorithms are developing in machine learning and deep neural networks. However, deep learning algorithms still have pressing problems to solve. That is, the data set is insufficient and of lo...
Currently, deep learning algorithms are developing in machine learning and deep neural networks. However, deep learning algorithms still have pressing problems to solve. That is, the data set is insufficient and of low quality for machine learning. One of the ways to solve this problem is to data augmentation the dataset. There are two types of image data sets: labeled data sets and unlabeled data sets. These annotations are important for object recognition. Deep learning algorithms typically use an annotated dataset. Similarly, the You Only Look Once (YOLOv5) network model also requires an annotated dataset. In this article, we manually created annotations for each image using the labelImg software tool. Different countries have different Traffic signs. The dataset of traffic signs of Uzbekistan (UTSD) has not yet been developed. Therefore, in this work, we developed a UTSD dataset for use in a traffic sign detection and recognition system (TSDR). The UTSD dataset contains 3957 Traffic sign images belonging to 56 classes. We improved the UTSD dataset by data augmentation.
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