This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change of Mr was highly dependent on NMAS and the thermo-rheological properties of the asphalt cement. Initially, a linear regression model was developed; however, it underestimated low Mr values and overestimated high Mr values. Moreover, the linear model resulted in negative Mr values, indicating an inadequate representation of the relationship between Mr and predictor variables. Consequently, a nonlinear transformed regression framework was employed to develop an equation that more accurately predicted the Mr values of WMA mixtures. The resulting predictive model exhibited a coefficient of determination (R2) of approximately 95 %. To validate the effectiveness of the proposed model, the remaining 30 % of the test data was utilized. The results demonstrated that the developed model effectively represented the observed data not used during the model-building process. This validation was supported by an R2 of 95.8 % between the predicted and measured Mr values of WMA mixtures.
Summary The paper proposes a small custom CNN for classifying solid waste into four classes: aluminum, cardboard, plastic, and glass. It is designed for real-time use on limited hardware such as a Raspberry Pi or Jetson.
Naturally carbonate reservoirs have very low oil recovery efficiency owing to their wettability and tightness of matrix. However, adding surfactant to brine solution can enhance oil recovery by changing the wettability of the carbonate rock surface from oil-wet to water-wet. In the present study, the effects of different brines in the presence of surfactant hexadecyltrimethylammonium bromide (CTAB), on the wettability of carbonate rock were investigated through different characteristics such as surface tension interfacial tension and contact angle. The best concentration of CTAB was investigated at 500 ppm in brine (NaCl) reduced surface tension and interfacial tensions to 42 mN/m and 15 mN/m respectively and prevented reservoir fro
... Show MoreTerahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope
... Show MoreThis work aims to find a solution to the problem under investigation and to study non-local boundary-value problems for rectangular domains and two-dimensional thirdorder partial differential equations (PDEs). A finite-difference method combined with the trapezoidal rule is used to solve problems. The numerical results were determined to be steady and accurate.
Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance
... Show MoreThere are a few studies that discuss the medical causes for diabetic foot (DF) ulcerations in Iraq, one of them in Wasit province. The aim of our study was to analyze the medical, therapeutic, and patient risk factors for developing DF ulcerations among diabetic patients in Baghdad, Iraq.