In this work, some mechanical properties of the polymer coating were improved by preparing a hybrid system containing Graphene (GR) of different weight percentages (0.25, 0.5, 1, and 2wt%) with 5wt% carbon fibres (CF) and added to a polymer coating by using casting method. The properties were improved as GR was added with further improvement on adding 5wt% of CF. The impact strength of acrylic polymer with GR increases with increasing weight ratio of GR; maximum value was obtained when the polymer coating was incorporated with 1wt% GR and 5wt% CF. The impact strength of acrylic polymer with GR and GR/CF composites incorporated with GR at 1wt% and CF at 5wt%. Hardness increase with increasing weight ratio of Gr and a significant improvement was observed at 1wt% GR and 5wt% CF content. The tensile strength increases more significantly than the acrylic polymer with GR and GR/CF composites incorporated with GR at 1wt% and CF at 5wt%. Pull-off strength for the polymer coating with GR and CF was greater than for the acrylic polymer coating.
An experiment was carried out to study the effect of soil organic carbon (SOC) and soil texture on the distance of the wetting front, cumulative water infiltration (I), infiltration rate (IR), saturated water conductivity (Ks), and water holding capacity (WHC). Three levels ( 0, 10, 20, and 30 g OC kg-1 ) from organic carbon (OC) were mixed with different soil materials sandy, loam, and clay texture soils. Field capacity (FC) and permanent wilting point (PWP) were estimated. Soil materials were placed in transparent plastic columns(12 cm soil column ), and water infiltration(I) was measured as a function of time, the distance of the wetting front and Ks. Results showed that advance we
Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreIn this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra
... Show MoreThe purpose of this paper is to develop a hybrid conceptual model for building information modelling (BIM) adoption in facilities management (FM) through the integration of the technology task fit (TTF) and the unified theory of acceptance and use of technology (UTAUT) theories. The study also aims to identify the influence factors of BIM adoption and usage in FM and identify gaps in the existing literature and to provide a holistic picture of recent research in technology acceptance and adoption in the construction industry and FM sector.
Abstract
For sparse system identification,recent suggested algorithms are
-norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MoreLow oil extraction and early high water production are caused in part by reservoir heterogeneity. Huge quantities of water production are prevalent issues that happen in older reservoirs. Polyacrylamide polymer gel systems have been frequently employed as plugging agents in heterogeneous reservoirs to regulate water output and increase sweep efficiency. Polyacrylamide polymer gel systems are classified into three classes depending on their composition and application conditions, which are in-situ monomer gel, in-situ polymer gel, and preformed particle gel (PPG).
This paper gives a comprehensive review of PPG’s status, preparation, and mechanisms. Many sorts of PPGs are categorized, for example, millimeter-sized preformed p
... Show MoreIn this study, NaOH dissolution method was applied to dissolve cellulose fibers which extracted from date palm fronds (type Al-Zahdi) taken from Iraqi gardens. In this process, (NaOH)-solution is brought into contact with the cellulose fibers at low temperature. Experiments were conducted with different concentrations of NaOH (4%, 6%, 8% and12%) weight percent at two cooling bath temperatures (-15 oC) and (-20oC). Maximum cellulose dissolution was 23 wt% which obtained at 8 wt% concentration of NaOH and at cooling bath temperature of -20oC. In order to enhance the cellulose fibers dissolution, the sample was pretreated with Fenton's reagent which consists of hydrogen peroxide (H2O2), oxalic acid (C2H2O4) and ferrous sulfate (FeSO4). This
... Show MoreIn this study, NaOH dissolution method was applied to dissolve cellulose fibers which extracted from date palm fronds (type Al-Zahdi) taken from Iraqi gardens. In this process, (NaOH)-solution is brought into contact with the cellulose fibers at low temperature. Experiments were conducted with different concentrations of NaOH (4%, 6%, 8% and12%) weight percent at two cooling bath temperatures (-15 oC) and (-20oC). Maximum cellulose dissolution was 23 wt% which obtained at 8 wt% concentration of NaOH and at cooling bath temperature of -20oC. In order to enhance the cellulose fibers dissolution, the sample was pretreated with Fenton's reagent which consists of
... Show MoreIn this study, NaOH dissolution method was applied to dissolve cellulose fibers which extracted from date palm fronds (type Al-Zahdi) taken from Iraqi gardens. In this process, (NaOH)-solution is brought into contact with the cellulose fibers at low temperature. Experiments were conducted with different concentrations of NaOH (4%, 6%, 8% and12%) weight percent at two cooling bath temperatures (-15 oC) and (-20oC). Maximum cellulose dissolution was 23 wt% which obtained at 8 wt% concentration of NaOH and at cooling bath temperature of -20oC. In order to enhance the cellulose fibers dissolution, the sample was pretreated with Fenton's reagent which consists of
... Show More