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| 1 | Some exact solutions of the oscillatory motion of a generalized second grade fluid in an annular region of two cylinders显示文摘The velocity field and the associated shear stress corresponding to the longitudinal oscillatory flow of a generalized second grade fluid,between two infinite coaxial circular cylinders,are determined by means of the Laplace and Hankel transforms.Initially,the fluid and cylinders are at rest and at t = 0+ both cylinders suddenly begin to oscillate along their common axis with simple harmonic motions having angular frequencies 1 and 2.The solutions that have been obtained are presented under integral and series forms in terms of the generalized G and R functions and satisfy the governing differential equation and all imposed initial and boundary conditions.The respective solutions for the motion between the cylinders,when one of them is at rest,can be obtained from our general solutions.Furthermore,the corresponding solutions for the similar flow of ordinary second grade fluid and Newtonian fluid are also obtained as limiting cases of our general solutions.At the end,the effect of different parameters on the flow of ordinary second grade and generalized second grade fluid are investigated graphically by plotting velocity profiles. | A.Mahmood C.Fetecau N.A.Khan M.Jamil | 2010 | Acta Mechanica Sinica2010，26，4： | 4 |
| 2 | RADARSAT在地质遥感中的潜在用途显示文摘雷达遥感器能为地质工作提供有用的构造信息,因为其后向散射特征与地形和地表粗糙度有关,但这些特征取决于遥感器的成像参数,如视角和波长。星载雷达的性能到目前为止还是很有限的,没有提供地质人员所需的灵活的成像参数。加拿大最近发射的RADARSAT是第一颗装备有不同成像模式合成孔径雷达(SAR)的地球观测卫星、入射角、空间分辨率、成像面积和观测方向有多种选择。RADARSAT的目的包括用标准的成像扫描条带获取全球的立体数据。在地质填图和勘探方面,RADARSAT可通过调整成像参数使之与地物性质和所需信息相一致,本文对RADARSAT数据的这些优点进行了论述。 | 张金良 A.Mahmood S.Carboni | 1997 | 遥感信息1997，，3： | 1 |
| 3 | Trial of trefoil factor 3 enemas, in combination with oral 5‐aminosalicylic acid, for the treatment of mild‐to‐moderate left‐sided ulcerative colitis显示文摘 | A.Mahmood L.Melley A. J.Fitzgerald S.Ghosh R. J.Playford | 2005 | Alimentary Pharmacology & Therapeutics2005，，11： | 1 |
| 4 | Adaptive Deep Learning Model to Enhance Smart Greenhouse Agriculture显示文摘The trend towards smart greenhouses stems from various factors,including a lack of agricultural land area owing to population concentration and housing construction on agricultural land,as well as water shortages.This study proposes building a full farming adaptation model that depends on current sensor readings and available datasets from different agricultural research centers.The proposed model uses a one-dimensional convolutional neural network(CNN)deep learning model to control the growth of strategic crops,including cucumber,pepper,tomato,and bean.The proposed model uses the Internet of Things(IoT)to collect data on agricultural operations and then uses this data to control and monitor these operations in real time.This helps to ensure that crops are getting the right amount of fertilizer,water,light,and temperature,which can lead to improved yields and a reduced risk of crop failure.Our dataset is based on data collected from expert farmers,the photovoltaic construction process,agricultural engineers,and research centers.The experimental results showed that the precision,recall,F1-measures,and accuracy of the one-dimensional CNN for the tested dataset were approximately 97.3%,98.2%,97.25%,and 97.56%,respectively.The new smart greenhouse automation system was also evaluated on four crops with a high turnover rate.The system has been found to be highly effective in terms of crop productivity,temperature management and water conservation. | Medhat A.Tawfeek Nacim Yanes Leila Jamel Ghadah Aldehim Mahmood A.Mahmood | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 5 | On the Effect of Mist Flow on the Heat Transfer Performances of a Three-Copper- Sphere Configuration显示文摘The cooling of a(pebble bed)spent fuel in a high-temperature gas-cooled reactor(HTGR)is adversely affected by an increase in the temperature of the used gas(air).To investigate this problem,a configuration consisting of three copper spheres arranged in tandem subjected to a forced mistflow inside a cylindrical channel is considered.The heat transfer coefficients and related variations as a function of Reynolds number are investigated accord-ingly.The experimental results show that when compared to those with only airflow,the heat transfer coefficient of the spherical elements with mistflow(j=112 kg/m2 hr,Re=55000)increases by 180%,75%,and 20%,respec-tively for thefirst,second,and third spherical element(the corresponding heat transfer enhancement ratio being 2.3,1.4,and 1.1).Additional numerical simulations reveal that the presence of stagnant zones with intense vortex formation around each spherical element contributes significantly to determine the heat transfer behavior. | Karema A.Hamad Yasser A.Mahmood | 2023 | Fluid Dynamics & Materials Processing2023，19，11： | 0 |
| 6 | Texture of the nano-crystalline AlN thin films and the growth conditions in DC magnetron sputtering显示文摘DC reactive magnetron sputtering technique has been used for the preparation of Al N thin fi lms. The deposition temperature and the fl ow ratio of N2/Ar were varied and subsequent dependency of the fi lms crystallites orientation/texture has been addressed. In general, deposited fi lms were found hexagonal polycrystalline with a(002) preferred orientation. The X-ray diffraction(XRD) data revealed that the fi lm crystallinity improves,with the increase of substrate temperature from 300 ℃to 500℃. The dropped in full width half maximum(FWHM) of the XRD rocking curve value further con fi rmed it. However, increasing substrate temperature above 500 ℃or reducing the nitrogen condition(from 60 to 30% in the environment) induced the growth of crystallites with(102) and(103) orientations. The rise of rocking curve FWHM for the corresponding conditions depicted that the fi lms texture quality deteriorated. A further con fi rmation of the variation in fi lm texture/orentation with the growth conditions has been obtained from the variation in FWHM values of a dominant E1(TO) mode in the Fourier transform infrared(FTIR) spectra and the E2(high) mode in Raman spectra. We have correlated the columnar structure in AFM surface analyses with the(002) or c-axis orientation as well. Spectroscopic ellipsometry of the samples have shown a higher refractive index at 500 ℃growth temperature. | Shakil Khan Muhammad Shahid A.Mahmood A.Shah Ishaq Ahmed Mazhar Mehmood U.Aziz Q.Raza M.Alam | 2015 | Progress in Natural Science:Materials International2015，25，4： | 0 |
| 7 | Structural and optical analysis of Cr_2N thin films prepared by DC magnetron sputtering显示文摘Chromium nitride(Cr2N) thin films were prepared by a DC magnetron sputtering technique. The deposition temperature was raised from 50 to 300°C, and its influence on the film structure and refractive index was investigated. X-ray diffraction analysis shows that the crystalline structure of the films transforms from the(101) to(002) oriented hexagonal Cr2 N phase as the increase of substrate temperature above 50°C, and a highly textured film grows at 100°C. An empirical relation between the crystalline orientation and infrared active modes of the films is obtained, i.e., the Fourier transform infrared(FTIR) spectrum of the film prepared at 50°C exhibits only A1(TO) mode. The prominent peak in the FTIR spectra of the film prepared above 50°C is assigned to the E1(TO) mode and is correlated with the(002) or c-axis oriented hexagonal wurtzite phase of Cr2 N. In the surface analysis of atomic force microscopy, a transformation from the featureless surface to columnar-type morphology is observed with the increase of substrate temperature from 50 to 100°C, exhibiting c-axis oriented crystallite growth. A further increase in substrate temperature to 200°C causes the c-axis crystallites to merge, resulting in the formation of voids. The refractive index(n) of the deposited films is obtained using spectroscopic ellipsometry. | Shakil Khan A.Mahmood A.Shah Qaiser Raza Muhammad Asim Rasheed Ishaq Ahmad | 2015 | International Journal of Minerals,Metallurgy and Materials2015，22，2： | 0 |
| 8 | Olive Leaf Disease Detection via Wavelet Transform and Feature Fusion of Pre-Trained Deep Learning Models显示文摘Olive trees are susceptible to a variety of diseases that can cause significant crop damage and economic losses.Early detection of these diseases is essential for effective management.We propose a novel transformed wavelet,feature-fused,pre-trained deep learning model for detecting olive leaf diseases.The proposed model combines wavelet transforms with pre-trained deep-learning models to extract discriminative features from olive leaf images.The model has four main phases:preprocessing using data augmentation,three-level wavelet transformation,learning using pre-trained deep learning models,and a fused deep learning model.In the preprocessing phase,the image dataset is augmented using techniques such as resizing,rescaling,flipping,rotation,zooming,and contrasting.In wavelet transformation,the augmented images are decomposed into three frequency levels.Three pre-trained deep learning models,EfficientNet-B7,DenseNet-201,and ResNet-152-V2,are used in the learning phase.The models were trained using the approximate images of the third-level sub-band of the wavelet transform.In the fused phase,the fused model consists of a merge layer,three dense layers,and two dropout layers.The proposed model was evaluated using a dataset of images of healthy and infected olive leaves.It achieved an accuracy of 99.72%in the diagnosis of olive leaf diseases,which exceeds the accuracy of other methods reported in the literature.This finding suggests that our proposed method is a promising tool for the early detection of olive leaf diseases. | Mahmood A.Mahmood Khalaf Alsalem | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
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