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Hepatobiliary Surgery and Nutrition 2018年第2期7卷 105-115页

作者： Fiammetta Soggiu Francesco Giovinazzo Jack Straiton Giulia Turri Jim Phillips bassam al-kari Irfan Ahmed Mohammad Habib Hepatobiliary and Pancreatic Surgery Unit NHS GrampianAberdeenUK Department of Radiology NHS GrampianAberdeenUK

Monosegment 4±1 Associating Liver Partition and Portal Vein ligation for Staged hepatectomy(alPPS)for bilateral colorectal liver metastases decreases the risk of drop-out of two stage hepatectomy,triggering a rapid and significant increase in future liver remnant(FLR)with promising oncological *** report two cases of segment 4+1 monosegment alPPS for multiple colorectal liver metastases performed at our *** the literature,seven similar cases have been *** and long term outcomes of our two patients were reported along with a review of data from the *** patients showed a FLR increase from 13%to 37%and from 14%to 41%of total liver volume,*** was compared to a median growth from 19%at baseline to 34%before stage 2,in the *** 20 and 27 months since resection both patients are alive and *** the literature,median overall survival and disease free survival were 13 months(range,5–24 months)and 5 months(range,3–23 months),*** 4±1 alPPS is associated with promising oncological outcomes and a significant FLR *** may be safely performed in selected patients as a salvage procedure,reducing the risk of the dropout of two-stage hepatectomy.

关键词： Associating Liver Partition and Portal Vein ligation for Staged hepatectomy(alPPS) liver resection colorectal liver metastases

Using Remote Sensing Data to Delineate the Lineaments for Hydrothermal Mineral Prediction in Heqing Area, Northwest Yunnan Province, China

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Journal of China University of Geosciences 2007年第2期18卷 142-147页

作者： Mansour S al-Mokredi 胡光道 bassam F al bassam Faculty of Earth Resources China University of Geosciences

Lineament extraction and analysis is one of the routine work in mapping medium and large areas using remote sensing data, most of which are satellite images. Landsat Enhanced Thematic Mapper （ETM） of 945×1 232 pixels subscene acquired on 21 March 2000 covering the northwestern part of Yunnan Province has been digitally processed using ER Mapper software. This article aims to produce lineament density map that predicts favorable zones for hydrothermal mineral occurrences and quantify spatial associations between the known hydrothermal mineral deposits. In the process of lineament extraction a number of image processing techniques were applied. The extracted lineaments were imported into MapGIS software and a suitable grid of 100 m×100 m was chosen. The Kriging method was used to create the lineament density map of the area. The results show that remote sensing data could be useful to extract the lineaments in the area. These lineaments are closely correlated with the faults obtained through other geological investigation methods. On comparing with field data the lineament-density map identifies two important high prospective zones, where large-scale deposits are already existing. In addition the map highlights unrecognized target areas that require follow up investigation.

关键词： lineament extraction hydrothermal mineral prediction Kriging method Heqing area(China)

Improved Geological Interpretation Using Landsat TM Data in Lancang-Jinghong Area, Yunnan Province, China

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Journal of China University of Geosciences 2003年第1期14卷 52-58页

作者： bassam F al bassam Faculty of Earth Resources China Universityof Geosciences

Landsat TM digital spectral data of Lancang Jinghong area (Yunnan P ro vince) has been used for the purpose of geological interpretation. To meet this object, different image processing techniques including selected band color comp osites, principal component analysis and IHS decorrelation stretching are used t o improve the discrimination of different lithological and structural features i n the *** was found that IHS decorrelation stretching images obtained from t he transformation of false color composite 741 (in red, green and blue) prov ided the best results based on the original *** combining the characteristic s of images produced by different approaches and other canonically transformed i mages with available geological data and surface observations, the geological in terpretation could be done with satisfactory degree of accuracy.

关键词： Landsat TM color composite images principal component analysis (PCA) IHS decorrelation stretching Lancang Jinghong China.

GIS Predictive Model for Producing Hydrothermal Gold Potential Map Using Weights of Evidence Approach in Gengma Region, Sanjiang District, China

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Journal of China University of Geosciences 2003年第3期14卷 283-292页

作者： bassam F al bassam Faculty of Earth Resources

Gengma region, Sanjiang district is known to have some large-scale gold deposits. GIS predictive model for hydrothermal gold potential was carried out in this region using weights of evidence modeling technique. Datasets used include large-scale hydrothermal gold deposit records, geological, geophysical and remote sensing imagery. Based on the geological and mineral characteristics of areas with known gold occurrences in Sanjiang, several geological features were thought to be indicative of areas with potential for the occurrence of hydrothermal gold deposits. Indicative features were extracted from geoexploration datasets for use as input in the predictive model. The features include host rock lithology, geologic structures, wallrock alteration and associated (volcanic-plutonic) igneous rocks. To determine which of the indicative geological features are important spatial predictors of area with potential for gold deposits, spatial analysis was done through the modeling method. The input maps were buffered and the optimum distance of spatial association for each geological feature was determined by calculating the contrast and studentized contrast. Five feature maps were converted to binary predictor patterns and used as evidential layers for predictive modeling. The binary patterns were integrated in two combinations, each of which consists of four patterns in order to avoid over prediction due to the effect of duplicate features in the two structural evidences. The two produced potential maps define almost similar favorable zones. Areas of intersections between these zones in the two potential maps placed the highest predictive favorable zones in the region.

关键词： geographic information system weights of evidence mineral resource prediction Sanjiang district

Chaotic Krill Herd with Deep Transfer Learning-Based Biometric Iris Recognition System

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Computers, Materials & Continua 2022年第12期73卷 5703-5715页

作者： Harbi al-Mahafzah Tamer AbuKhalil bassam A.Y.alqaralleh Department of Computer Science Faculty of Information TechnologyAl-Hussein Bin Talal University Ma’an71111Jordan MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia

Biometric verification has become essential to authenticate the individuals in public and private *** several biometrics,iris has peculiar features and its working mechanism is complex in *** recent developments in Machine Learning and Deep Learning approaches enable the development of effective iris recognition *** this motivation,the current study introduces a novel Chaotic Krill Herd with Deep Transfer Learning Based Biometric Iris Recognition System(CKHDTL-BIRS).The presented CKHDTL-BIRS model intends to recognize and classify iris images as a part of biometric *** achieve this,CKHDTL-BIRS model initially performs Median Filtering(MF)-based preprocessing and segmentation for iris *** addition,MobileNetmodel is also utilized to generate a set of useful feature ***,Stacked Sparse Autoencoder(SSAE)approach is applied for *** last,CKH algorithm is exploited for optimization of the parameters involved in SSAE *** proposed CKHDTL-BIRS model was experimentally validated using benchmark dataset and the outcomes were examined under several *** comparison study results established the enhanced performance of CKHDTL-BIRS technique over recent approaches.

关键词： Biometric verification iris recognition deep learning parameter tuning machine learning

Optimal Deep Learning Based Inception Model for Cervical Cancer Diagnosis

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Computers, Materials & Continua 2022年第7期72卷 57-71页

作者： Tamer AbuKhalil bassam A.Y.alqaralleh Ahmad H.al-Omari Computer Science Department Faculty of Information TechnologyAl Hussein bin Talal UniversityMa’an71111Jordan MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia Faculty of Science Computer Science DepartmentNorthern Border UniversityArar91431Saudi Arabia

Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear *** smear test analysis is laborious and tiresome work performed visually using a ***,automated cervical cancer diagnosis using automated methods are *** paper designs an optimal deep learning based Inception model for cervical cancer diagnosis(ODLIM-CCD)using pap smear *** proposed ODLIM-CCD technique incorporates median filtering(MF)based pre-processing to discard the noise and Otsu model based segmentation ***,deep convolutional neural network(DCNN)based Inception with Residual Network(ResNet)v2 model is utilized for deriving the feature ***,swallow swarm optimization(SSO)based hyperparameter tuning process is carried out for the optimal selection of ***,recurrent neural network(RNN)based classification process is done to determine the presence of cervical cancer or *** order to showcase the improved diagnostic performance of the ODLIM-CCD technique,a series of simulations occur on benchmark test images and the outcomes highlighted the improved performance over the recent approaches with a superior accuracy of 0.9661.

关键词： Median filtering convolutional neural network pap smear cervical cancer

Solutes in native plants in the Arabian Gulf region and the role of microorganisms: future research

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Journal of Plant Ecology 2018年第5期11卷 671-684页

作者： Roda Fahad al-Thani bassam Taha Yasseen Department of Biological and Environmental Sciences College of Arts&SciencesQatar UniversityDohaQatar Present address:8 James Court Dunstable RoadLuton LU40HNUK.

Aims One of the outstanding challenges facing humankind is increas-ing crop production under various types of severe environmental *** measures have been taken to adopt molecular and biotechnological approaches that lead to the development of transgenic plants able to deal with such harsh and polluted ***,such solutions could be very expensive and require considerable efforts and time to achieve these *** main objective of this review is to discuss the new biological solutions that have emerged in the last decade,as environmentally friendly approaches,perhaps to support and/or replace the present *** solutions based on plant-microbe interactions could be a lifeline and promising alternative strategy to create plants with a high resistance to the extreme *** During the last two decades research projects have been conducted to study the ecology,identify the features,and the ecophysiology of native plants and the associated microorganisms in the Arabian Gulf region and particularly in *** physiological and bio-chemical parameters have been determined,including organic sol-utes(amino acids like proline,glycinebetaine,soluble sugars,etc.),photosynthetic pigments,organic acids and inorganic ions espe-cially heavy metals,along with the physical and chemical proper-ties of the soil in various locations of the State of ***,the microorganisms adjacent to and associated with these native plants were identified to elucidate the possible roles in the soil biota in supporting these plants against extreme environmental *** Findings Investigations of native plants in the Arabian Gulf states during the last decade have shown that wild plants exhibit different abili-ties to accumulate organic solutes to cope with the harsh natural *** is a major factor stressing wildlife in this region due to the expansion of urban sectors and industrial activi-ties of oil and ***

关键词： Arabian Gulf region arid lands compatible solutes drought microorganisms modern approaches pollution salinity

Evolutionary Intelligence and Deep Learning Enabled Diabetic Retinopathy Classification Model

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Computers, Materials & Continua 2022年第10期73卷 87-101页

作者： bassam A.Y.alqaralleh Fahad aldhaban Anas Abukaraki Esam A.al.Qaralleh MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia Department of Computer Science Faculty of Information TechnologyAl-Hussein Bin Talal UniversityMa’an71111Jordan School of Engineering Princess Sumaya University for TechnologyAmman11941Jordan

Diabetic Retinopathy(DR)has become a widespread illness among diabetics across the *** fundus images are generally used by physicians to detect and classify the stages of *** manual examination of DR images is a time-consuming process with the risks of biased results,automated tools using Artificial Intelligence(AI)to diagnose the disease have become *** this view,the current study develops an Optimal Deep Learning-enabled Fusion-based Diabetic Retinopathy Detection and Classification(ODL-FDRDC)*** intention of the proposed ODLFDRDC technique is to identify DR and categorize its different grades using retinal fundus *** addition,ODL-FDRDC technique involves region growing segmentation technique to determine the infected ***,the fusion of two DL models namely,CapsNet and MobileNet is used for feature ***,the hyperparameter tuning of these models is also performed via Coyote Optimization algorithm(COA).Gated Recurrent Unit(GRU)is also utilized to identify *** experimental results of the analysis,accomplished by ODL-FDRDC technique against benchmark DR dataset,established the supremacy of the technique over existing methodologies under different measures.

关键词： Optimization algorithms medical images diabetic retinopathy deep learning fusion model

Optimized parallel architecture of evolutionary neural network for mass spectrometry data processing

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International Journal of Modeling, Simulation, and Scientific Computing 2017年第1期8卷 231-257页

作者： Amin Jarrah Bashar Haddad Mohammad A.al-Jarrah Muhammad bassam Obeidat Department of Computer Engineering Yarmouk University Irbid 21163Jordan Computer Engineering Department The University of Jordan Amman 11942Jordan Department of Computer Engineering Jordan University of Science and Technology Irbid 22110 Jordan

Evolutionary neural network(ENN)shows high performance in function optimization and in finding approximately global optima from searching large and complex *** is one of the most efficient and adaptive optimization techniques used widely to provide candidate solutions that lead to the fitness of the *** has the extraordinary ability to search the global and learning the approximate optimal solution regardless of the gradient information of the error ***,ENN requires high computation and processing which requires parallel processing platforms such as field programmable gate arrays(FPGAs)and graphic processing units(GPUs)to achieve a good *** work involves different new implementations of ENN by exploring and adopting different techniques and opportunities for parallel *** versions of ENN algorithm have also been implemented and parallelized on FPGAs platform for low latency by exploiting the parallelism and pipelining *** data form mass spectrometry data(MSD)application was tested to examine and verify our *** is a very important and extensive computation application which needs to search and find the optimal features(peaks)in MSD in order to distinguish cancer patients from control *** algorithm is also implemented and parallelized on single core and GPU platforms for comparison *** computation time of our optimized algorithm on FPGA and GPU has been improved by a factor of 6.75 and 6,respectively.

关键词： Genetic algorithm neural networks evolutionary neural network fieldprogrammable gate array(FPGA) graphic processing unit(GPU) parallel architecture optimization techniques

Multi-scale fractures formation and distribution in tight sandstones—a case study of Triassic Chang 8 Member in the southwestern Ordos Basin

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Frontiers of Earth Science 2022年第2期16卷 483-498页

作者： Gaojian XIAO Ling HU Yang LUO Yujing MENG ali bassam Taher al-SalAFI Haoran LIU Key Laboratory of Tectonics and Petroleum Resources China University of GeosciencesWuhan 430074China Wenhua College Wuhan 430074China Faculty of Petroleum and Natural Resources Sana’a UniversitySana’aYemen Louisiana State University Baton Rouge LA 7080USA

Fracture system is an important factor controlling tight oil accumulation in the Triassic Chang 8 Member,southwestern Ordos Basin,China.A systematic characterization of the multi-scale natural fractures is a basis for the efficient tight oil *** on outcrops,seismic reflections,well cores,well logs(image and conventional logging),casting thin sections,and scanning electron microscope observation,the multi-scale fractures occurrences and their influences on Chang 8 tight sandstone reservoirs are *** results show that three periods of strike-slip faults and four scales of natural fractures developed,namely mega-scale(length>7×10^(7) mm),macro-scale(3.5×10^(5)ale(10ale(lengthale fractures developed by strike-slip faults are characterized by strike-segmentation and lateral zonation,which connect the source and *** scale fractures also influence the distribution and effectiveness of traps and reservoirs,which directly influence the hydrocarbon charging and *** meso fractures include the tectonic,diagenetic,as well as hydrocarbon generation-related overpressure *** meso-and micro-scale fractures improve the sandstone physical properties and also the tight oil well production *** integrated study helps to understand the distribution of multi-scale fractures in tight sandstones and provides a referable case and workflow for multi-scale fracture evaluation.

关键词： natural fractures characteristics geological significance tight sandstone reservoir Upper Triassic Yanchang Formation