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Will artificial intelligence reach any limit in gastroenterology?

Artificial Intelligence in Gastroenterology 2024年第2期5卷 1-9页

作者： Joseph Bou Jaoude Rose al Bacha bassam Abboud Department of Gastroenterology Levant HospitalBeirut 166830Lebanon Department of General Surgery Geitaoui HospitalFaculty of MedicineLebanese UniversityLebanonBeirut 166830Lebanon

Endoscopy is the cornerstone in the management of digestive *** the last few decades,technology has played an important role in the development of this field,helping endoscopists in better detecting and characterizing luminal ***,despite ongoing advancements in endoscopic technology,the incidence of missed pre-neoplastic and neoplastic lesions remains high due to the operator-dependent nature of endoscopy and the challenging learning curve associated with new *** intelligence(AI),an operator-independent field,could be an invaluable *** can serve as a“second observer”,enhancing the performance of endoscopists in detecting and characterizing luminal *** utilizing deep learning(DL),an innovation within machine learning,AI automatically extracts input features from targeted endoscopic *** encompasses both computer-aided detection and computer-aided diagnosis,assisting endoscopists in reducing missed detection rates and predicting the histology of luminal digestive *** applications in clinical gastrointestinal diseases are continuously expanding and evolving the entire digestive *** all published studies,real-time AI assists endoscopists in improving the performance of non-expert gastroenterologists,bringing it to a level comparable to that of *** development of DL may be affected by selection *** have utilized different AI-assisted models,which are *** the future,algorithms need validation through large,randomized ***,AI has no limit to assist endoscopists in increasing the accuracy and the quality of endoscopic ***,practically,we still have a long way to go before standardizing our AI models to be accepted and applied by all gastroenterologists.

关键词： Artificial intelligence Digestive tract Gastroenterology Gastroscopy Coloscopy

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Low-Density Microplastics in Recreational Parks of.al Ain, United Arab Emirates: Abundance, Composition, and Potential Effects on Soil Health

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Journal of Environmental Protection 2024年第2期15卷 109-123页

作者： Rener De Jesus Ahmed Abuibaid bassam al-Hindawi Ruwaya alKendi Department of Biology College of Science United Arab Emirates University Al Ain UAE Department of Chemistry College of Science United Arab Emirates University Al Ain UAE

Microplastics (MPs) have been an emerging concern due to their harmful effects on the ecosystem and are ubiquitous in various habitats, from marine to terrestrial environments. However, studies on the presence of MPs in recreational areas are limited. One of the previous works has reported that urban recreational parks are considered “sinks” for plastic debris, including MPs. In this study, low-density MPs (LD-MPs) in soil samples collected from recreational parks of.al Ain, United Arab Emirates (UAE) were isolated by density flotation method. Results showed that these parks have varying levels of LD-MPs caused by various anthropogenic activities, such as sludge use and application of reclaimed water from wastewater treatment facilities in those areas. These plastic particles were isolated in 87% of the soil samples, with an average concentration of 1550 ± 340 MPs/kg. Predominantly, these comprised large LD-MPs (300 - 5000 μm), with red and blue being the most common colors. fourier transform infrared (fTIR) spectroscopy identified possible synthetic polymers, including polyethylene and polypropylene. Additionally, a negative correlation was observed between LD-MP concentration and soil pH and moisture content, indicating potential adverse effects on soil health. These findings highlight the need for monitoring and managing microplastic pollution in urban recreational areas to mitigate its ecological impacts.

关键词： Plastic Particles fTIR Analysis Microfibers Soil Pollutants Urban Parks

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Phishing Attacks Detection Using EnsembleMachine Learning algorithms

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Computers, Materials & Continua 2024年第7期80卷 1325-1345页

作者： Nisreen Innab Ahmed Abdelgader fadol Osman Mohammed Awad Mohammed Ataelfadiel Marwan Abu-Zanona bassam Mohammad Elzaghmouri farah H.Zawaideh Mouiad fadeil alawneh Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26110Jordan Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan faculty of Information Technology Ajloun National UniversityAjloun26767Jordan

Phishing,an Internet fraudwhere individuals are deceived into revealing critical personal and account information,poses a significant risk to both consumers and web-based *** indicates a persistent rise in phishing ***,these fraudulent schemes are progressively becoming more intricate,thereby rendering them more challenging to ***,it is imperative to utilize sophisticated algorithms to address this *** learning is a highly effective approach for identifying and uncovering these harmful *** learning(ML)approaches can identify common characteristics in most phishing *** this paper,we propose an ensemble approach and compare it with six machine learning techniques to determine the type of website and whether it is normal or not based on two phishing *** that,we used the normalization technique on the dataset to transform the range of.all the features into the same *** findings of this paper for all algorithms are as follows in the first dataset based on accuracy,precision,recall,and f1-score,respectively:Decision Tree(DT)(0.964,0.961,0.976,0.968),Random forest(Rf)(0.970,0.964,0.984,0.974),Gradient Boosting(GB)(0.960,0.959,0.971,0.965),XGBoost(XGB)(0.973,0.976,0.976,0.976),AdaBoost(0.934,0.934,0.950,0.942),Multi Layer Perceptron(MLP)(0.970,0.971,0.976,0.974)and Voting(0.978,0.975,0.987,0.981).So,the Voting classifier gave the best *** in the second dataset,all the algorithms gave the same results in four evaluation metrics,which indicates that each of them can effectively accomplish the prediction ***,this approach outperformed the previous work in detecting phishing websites with high accuracy,a lower false negative rate,a shorter prediction time,and a lower false positive rate.

关键词： Social engineering attacks phishing attacks machine learning security artificial intelligence

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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)

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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.

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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

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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

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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

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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

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Analysis of OECD/NEA medium 1000 MWth sodium-cooled fast reactor using the Monte Carlo serpent code and ENDf/B-VIII.0 nuclear data library

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Nuclear Science and Techniques 2020年第12期31卷 77-87页

作者： fatima Ial-Hamadi bassam AKhuwaileh Peng Hong Liem Donny Hartanto Department of Mechanical and Nuclear Engineering University of SharjahP.O.BOX 27272SharjahUnited Arab Emirates Graduate School of Engineering Cooperative Major in Nuclear EnergyTokyo City University(TCU)1-28-1 TamazutsumiSetagayaTokyoJapan Scientific Computational Division Nippon Advanced Information Service(NAIS Co.Inc.)416 MuramatsuTokaimuraIbarakiJapan

This study presents a benchmark evaluation of the new ENDf/B-VIII.0 nuclear data library for the Organization for Economic Co-operation and Development/Nuclear Energy Agency Medium 1000 MWth sodium-cooled fast reactor(SfR).The study presented herein covers both SfR core types,i.e.,metallic fueled(MET-1000)and oxide fueled(MOX-1000),simulated using the continuous-energy Monte Carlo Serpent2 *** neutronics performances of the ENDf/B-VIII.0-based simulations were compared mainly to two libraries:ENDf/B-VII.1 and *** comparison includes several neutronics parameters evaluated for the beginning and end of the cycle *** parameters include the effective multiplication factor keff,total effective delayed neutron fraction beff,sodium void reactivity(DqNa),Doppler constant(DqDoppler),and control rod worth(DqCR).In addition,a sensitivity study was used to reveal the major isotope/reaction pairs contributing to the discrepancy observed in the performance of the three libraries using 33 and 44-energy-group structures.

关键词： Serpent ENDf/B-VIII.0 Sodium-cooled fast reactor Sensitivity analysis

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