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| 1 | Probabilistic assessment of rock slopes stability using the response surface approach——A case study显示文摘This paper examines the stability condition of a jointed rock slope in the south western region of Saudi Arabia using deterministic and probabilistic approaches,under both dry and wet conditions.The study area is characterized by complex geology in rugged terrains.The stability analysis is carried out using the code FLAC3D to generate a 3-dimensional,ubiquitous joint model,to determine the influence of the dominant,unfavourable discontinuity orientation with respect to the slope face.The deterministic analysis is first implemented using the mean values of the selected random variables,namely the dip,dip direction and friction angle of the dominant discontinuity set,and the stability condition is assessed with a factor of safety based on the classical frictional joint constitutive model.A Box-Behnken design(BBD)approach is then adopted to create the surface response function as a second order polynomial for the factor of safety.To do so,fifteen FLAC3D models are generated in accordance with the BBD.Based on this,10,000 simulations of different slope realizations are carried out using Monte-Carlo simulation technique,and the probability of unsatisfactory of performance of the rock slope is assessed.It is shown that the probabilistic approach provides more insight and confidence in the stability condition of the rock slope,both under dry and steady state heavy rainfall conditions.A discussion is presented on the significance of accepting lower safety factors when heavy rainfall conditions are encountered. | Hassan Basahel Hani Mitri | 2019 | International Journal of Mining Science and Technology2019，29，3： | 7 |
| 2 | Application of rock mass classification systems to rock slope stability assessment:A case study显示文摘The stability of rock slopes is considered crucial to public safety in highways passing through rock cuts, as well as to personnel and equipment safety in open pit mines. Slope instability and failures occur due to many factors such as adverse slope geometries, geological discontinuities, weak or weathered slope materials as well as severe weather conditions. External loads like heavy precipitation and seismicity could play a significant role in slope failure. In this paper, several rock mass classification systems developed for rock slope stability assessment are evaluated against known rock slope conditions in a region of Saudi Arabia, where slopes located in rugged terrains with complex geometry serve as highway road cuts. Selected empirical methods have been applied to 22 rock cuts that are selected based on their failure mechanisms and slope materials. The stability conditions are identified, and the results of each rock slope classification system are compared. The paper also highlights the limitations of the empirical classification methods used in the study and proposes future research directions. | Hassan Basahel Hani Mitri | 2017 | Journal of Rock Mechanics and Geotechnical Engineering2017，9，6： | 4 |
| 3 | Effect ofZr4+doping on the stabilization of ZnCo-mixed oxide spinel systemand its catalytic activity towards N2O decomposition显示文摘 | Basahel S N Abd El-Maksod I H Abu-Zied B M | 2010 | Journal ofAlloys and Compounds2010，493，： | 1 |
| 4 | Ammo- nium ion exchange equilibrium on potassium zinc hexacyanoferrate(Ⅱ ) Kz Zn: 2 显示文摘 | Marei S A Basahel S N Rahmatallah A B | 1986 | J Ra- dioanal Nucl Chem1986，104，4： | 1 |
| 5 | Influence of crystal structure of nanosized ZrO 2 on photocatalytic degradation of methyl orange显示文摘 | Sulaiman N Basahel Tarek T Ali Mohamed Mokhtar Katabathini Narasimharao | 2015 | Nanoscale Research Letters2015，，1： | 1 |
| 6 | Effect of synthesis methods for mesoporous zirconia on its structural and textural properties显示文摘 | Mohamed Mokhtar Sulaiman N. Basahel Tarek T. Ali | 2013 | Journal of Materials Science2013，，6： | 1 |
| 7 | Nanostructured Mg-A1 hydrotalcite as catalyst for fine chemical synthesis显示文摘 | Sulaiman N Basahel Shaeel A A1-Thabaiti Katabathini Narasimharao | 2014 | J Nanosci Nano- technol2014，14，2： | 1 |
| 8 | Thermal decomposition of iron ( Ⅲ ) oxalate-magnesium oxalate mixtures 显示文摘 | BASAHEL S N EL-BELLIHI A A GABAL M | 1995 | Thermochimica Acta1995，256，2： | 1 |
| 9 | Thermal decomposition of iron(Ⅲ)oxalate-magnesium oxalate mixtures显示文摘 | Basahel S N El-Bellihi A A Gabal M | 1995 | Thermochimica acta1995，256，2： | 1 |
| 10 | Leveraging Retinal Fundus Images with Deep Learning for Diabetic Retinopathy Grading and Classification显示文摘Recently,there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy(DR).DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed world.Initial detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus images.This article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy(DLLSHDM-DR)on Retinal Fundus Images.The proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making method.In the DLLSHDM-DR technique,image preprocessing is initially performed to improve the quality of the fundus image.Besides,the DLLSHDM-DR applies HybridNet for producing a collection of feature vectors.For retinal image classification,the DLLSHDM-DR technique exploits the Emperor Penguin Optimizer(EPO)with a Deep Recurrent Neural Network(DRNN).The application of the EPO algorithm assists in the optimal adjustment of the hyperparameters related to the DRNN model for DR detection showing the novelty of our work.To assuring the improved performance of the DLLSHDMDR model,a wide range of experiments was tested on the EyePACS dataset.The comparison outcomes assured the better performance of the DLLSHDM-DR approach over other DL models. | Mohammad Yamin Sarah Basahel Saleh Bajaba Mona Abusurrah ELaxmi Lydia | 2023 | Computer Systems Science & Engineering2023，46，8： | 0 |
| 11 | Automated Artificial Intelligence Empowered White Blood Cells Classification Model显示文摘White blood cells (WBC) or leukocytes are a vital component ofthe blood which forms the immune system, which is accountable to fightforeign elements. The WBC images can be exposed to different data analysisapproaches which categorize different kinds of WBC. Conventionally, laboratorytests are carried out to determine the kind of WBC which is erroneousand time consuming. Recently, deep learning (DL) models can be employedfor automated investigation of WBC images in short duration. Therefore,this paper introduces an Aquila Optimizer with Transfer Learning basedAutomated White Blood Cells Classification (AOTL-WBCC) technique. Thepresented AOTL-WBCC model executes data normalization and data augmentationprocess (rotation and zooming) at the initial stage. In addition,the residual network (ResNet) approach was used for feature extraction inwhich the initial hyperparameter values of the ResNet model are tuned by theuse of AO algorithm. Finally, Bayesian neural network (BNN) classificationtechnique has been implied for the identification of WBC images into distinctclasses. The experimental validation of the AOTL-WBCC methodology isperformed with the help of Kaggle dataset. The experimental results foundthat the AOTL-WBCC model has outperformed other techniques which arebased on image processing and manual feature engineering approaches underdifferent dimensions. | Mohammad Yamin Abdullah M.Basahel Mona Abusurrah Sulafah M Basahel Sachi Nandan Mohanty E.Laxmi Lydia | 2023 | Computers, Materials & Continua2023，，4： | 0 |
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