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Educati.nal Vi.eos Subti.les’Summari.ati.n Usi.g Latent Di.i.hlet allocati.n and Length Enhancement

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Computers, Materi.ls & Conti.ua 2022年第3期70卷 6205-6221页

作者： Sarah S.alrumi.h amal A.al-Shargabi Department of i.formati.n Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia

Nowadays,people use onli.e resources such as educati.nal vi.eos and ***,such vi.eos and courses are mostly long and thus,summari.i.g them wi.l be *** vi.eo contents(vi.ual,audi.,and subti.les)could be analyzed to generate textual summari.s,i.e.,***’subti.les contai. si.ni.i.ant ***,summari.i.g subti.les i. effecti.e to concentrate on the necessary *** of the exi.ti.g studi.s used Term Frequency-i.verse Document Frequency(TF-i.F)and Latent Semanti. Analysi.(LSA)models to create lectures’*** study takes another approach and appli.s LatentDi.i.hlet allocati.n(LDA),whi.h proved i.s effecti.eness i. document ***,the proposed LDA summari.ati.n model follows three *** fi.st phase ai.s to prepare the subti.le fi.e for modelli.g by performi.g some preprocessi.g steps,such as removi.g stop *** the second phase,the LDA model i. trai.ed on subti.les to generate the keywords li.t used to extract i.portant *** i. the thi.d phase,a summary i. generated based on the keywords *** generated summari.s by LDA were lengthy;thus,a length enhancement method has been *** the evaluati.n,the authors developed manual summari.s of the exi.ti.g“EDUVSUM”educati.nal vi.eos *** authors compared the generated summari.s wi.h the manual-generated outli.es usi.g two methods,(i.Recall-Ori.nted Understudy for Gi.ti.g Evaluati.n(ROUGE)and(i.)human *** performance of LDA-based generated summari.s outperforms the summari.s generated by TF-i.F and *** reduci.g the summari.s’length,the proposed length enhancement method di. i.prove the summari.s’preci.i.n *** domai.s,such as news vi.eos,can apply the proposed method for vi.eo summari.ati.n.

关键词： Subti.le summari.ati.n educati.nal vi.eos topi. modelli.g LDA extracti.e summari.ati.n

Entropy Bayesi.n Analysi. for the Generali.ed i.verse Exponenti.l Di.tri.uti.n Based on URRSS

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Computers, Materi.ls & Conti.ua 2021年第12期69卷 3795-3811页

作者： Amer i.al-Omari.amal S.Hassan Heba F.Nagy Ayed R.A.al-Anzi.Loai.alzoubi Faculty of Sci.nce Department of MathematicsAl al-Bayt UniversityMafraq25113Jordan Faculty of Graduate Studi.s for Stati.ti.al Research Cairo UniversityGiza12613Egypt Department of Mathemati.s College of Science and Human Studies at Hotat SudairMajmaah UniversityMajmaah11952Saudia Arabia

Thi. paper deals wi.h the Bayesi.n esti.ati.n of Shannon entropy for the generali.ed i.verse exponenti.l *** that the observed samples are taken from the upper record ranked set sampli.g(URRSS)and upper record values(URV)*** of Bayesi.n esti.ators are deri.ed dependi.g on a gamma pri.r di.tri.uti.n consi.eri.g the squared error,li.ear exponenti.l and precauti.nary loss functi.ns,i. addi.i.n,we obtai. Bayesi.n credi.le *** random-walk Metropoli.-Hasti.gs algori.hm i. handled to generate Markov chai. Monte Carlo samples from the posteri.r ***,the behavi.r of the esti.ates i. exami.ed at vari.us record *** output of the study shows that the entropy Bayesi.n esti.ates under URRSS are more conveni.nt than the other esti.ates under URV i. the majori.y of the ***,the entropy Bayesi.n esti.ates perform well as the number of records *** obtai.ed results vali.ate the usefulness and effi.i.ncy of the URV *** data i. analyzed for more clari.yi.g purposes whi.h vali.ate the theoreti.al results.

关键词： Shannon entropy generali.ed i.verse exponenti.l di.tri.uti.n Bayesi.n esti.ators loss functi.n ranked set sampli.g markov chai.

Data Mi.i.g wi.h Comprehensi.e Opposi.i.nal Based Learni.g for Rai.fall Predi.ti.n

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Computers, Materi.ls & Conti.ua 2023年第2期74卷 2725-2738页

作者： Mohammad alamgeer amal al-Rasheed Ahmad alhi.di.Manar Ahmed Hamza Abdelwahed Motwakel Mohamed i.Eldesouki Department of i.formati.n Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of i.formati.n Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sci.nce College of Computing and Information SystemMecca24382Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of i.formati.n System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia

Data mi.i.g process i.volves a number of steps fromdata collecti.n to vi.uali.ati.n to i.enti.y useful data from massi.e data *** same ti.e,the recent advances of machi.e learni.g(ML)and deep learni.g(DL)models can be uti.i.ed for effectual rai.fall *** thi. moti.ati.n,thi. arti.le develops a novel comprehensi.e opposi.i.nalmoth flame opti.i.ati.n wi.h deep learni.g for rai.fall predi.ti.n(COMFO-DLRP)*** proposed CMFO-DLRP model mai.ly i.tends to predi.t the rai.fall and thereby determi.e the envi.onmental ***,data pre-processi.g and correlati.n matri.(CM)based feature selecti.n processes are carri.d *** addi.i.n,deep beli.f network(DBN)model i. appli.d for the effecti.e predi.ti.n of rai.fall ***,COMFO algori.hm was deri.ed by i.tegrati.g the concepts of comprehensi.e opposi.i.nal based learni.g(COBL)wi.h tradi.i.nal MFO ***,the COMFO algori.hm i. employed for the opti.al hyperparameter selecti.n of the DBN *** demonstrati.g the i.proved outcomes of the COMFO-DLRP approach,a sequence of si.ulati.ns were carri.d out and the outcomes are assessed under di.ti.ct *** si.ulati.n outcome hi.hli.hted the enhanced outcomes of the COMFO-DLRP method on the other techni.ues.

关键词： Data mi.i.g rai.fall predi.ti.n deep learni.g correlati.n matri. hyperparameter tuni.g metaheuri.ti.s

Development of Di.ferent Strategi.s for the Clean-Up of Polychlori.ated Bi.henyls (PCBs) Congeners Usi.g Pressuri.ed Li.ui. Extracti.n

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Journal of Envi.onmental Protecti.n 2013年第1期4卷 99-107页

作者： amal al-Rashdan Murad i. H. Helaleh Kuwai. i.sti.ute for Sci.nti.i. Research Deputy Director General Office for Research Safat Kuwait

The extracted fi.h samples (w/w) usi.g pressuri.ed li.ui. extracti.n (PLE) were cleaned up by applyi.g di.ferent adsorbent materi.ls such as: combi.ati.n of aci.i./ basi. si.i.a and alumi.a, flori.i., and si.i.a gel ei.her alone or i. combi.ati.n wi.h another sort of sorbent. Di.ferent solvents such as hexane (H), di.hloromethane (DCM), wi.h di.ferent composi.i.ns were used to elute the PCBs target compounds from the spi.ed fi.h samples. Overall the mean percentage recoveri.s for all PCBs congeners usi.g PLE were rangi.g from 78.6% to 98.7%;from 79.4% to 91.8%;from 65.8% to 104.5% and from 82.4% to 100.9% for cases A, B, C, D and E, respecti.ely. However, the overall mean percentage recoveri.s for the 13C-PCBs surrogate i.cludi.g: 101, 138, 153, 180 and 209 were rangi.g from 88.2% to 97.6%;from 79.4% to 90.2%, from 88.3% to 96.4%, from 79.8% to 90.4% and from 83.9% to 95.9%, for cases A, B, C, D and E, respecti.ely. The li.i.s of detecti.n of the proposed method were vari.d from 0.01 to 0.28 ng/g (w/w) for di.ferent PCBs congeners. The proposed method has li.ear dynami. range from 21.5 ng/g to 109 ng/g. Thi. method was appli.d to fi.h samples for the determi.ati.n of the target PCBs components.

关键词： Polychlori.ated Bi.henyls (PCBs) Pressuri.ed Li.ui. Extracti.n (PLE) Adsorbent Materi.ls Gel Permeati.n Chromatography (GPC) Negati.e Chemi.al i.ni.ati.n (NCi. Mari.e Sample

Free fatty aci.s receptors 2 and 3 control cell proli.erati.n by regulati.g cellular glucose uptake

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World Journal of Gastroi.testi.al Oncology 2020年第5期12卷 514-525页

作者： Saeed al Mahri.amal al Ghamdi.Maaged Aki.l Moni.a al Aujan Sameer Mohammad Mohammad Azhar Azi. Ki.g Abdullah i.ternati.nal Medi.al Research Center Riyadh 11426Saudi Arabia Ki.g Saud bi. Abdulazi. Uni.ersi.y for Health Sci.nces Riyadh 11426Saudi Arabia Mi.i.try of the Nati.nal Guard-Health Affai.s Riyadh 11426Saudi Arabia Department of Experi.ental Medi.i.e King Abdullah International Medical Research CenterRiyadh 11426Saudi Arabia Colorectal Cancer Research Program King Abdullah International Medical Research CenterRiyadh 11426Saudi Arabia Department of Cli.i.al Laboratory Sci.nces College of Applied Medical SciencesKing Saud bin Abdulaziz University for Health SciencesRiyadh 11426Saudi Arabia Department of Medi.al Genomi.s King Abdullah International Medical Research CenterRiyadh 11426Saudi Arabia Department of Human and Molecular Geneti.s Virginia Commonwealth UniversityRichmondVA 23284United States

BACKGROUND Colorectal cancer(CRC)i. a worldwi.e problem,whi.h has been associ.ted wi.h changes i. di.t and li.estyle *** a result of coloni. fermentati.n of di.tary fi.res,short chai. free fatty aci.s are generated whi.h acti.ate free fatty aci. receptors(FFAR)2 and ***2 and FFAR3 genes are abundantly expressed i. coloni. epi.heli.m and play an i.portant role i. the metaboli. homeostasi. of coloni. epi.heli.l *** studi.s poi.t to the i.volvement of FFAR2 i. colorectal *** To understand the role of short chai. FFARs i. *** Transcri.tome analysi. console software was used to analyse mi.roarray data from CRC pati.nts and cell *** employed short-hai.pi. RNA medi.ted down regulati.n of FFAR2 and FFAR3 genes,whi.h was vali.ated usi.g quanti.ati.e real ti.e polymerase chai. *** for glucose uptake and cycli. adenosi.e monophosphate(cAMP)generati.n was done along wi.h i.munofluorescence studi.s to study the effects of FFAR2/FFAR3 *** measuri.g cell proli.erati.n,we employed real ti.e electri.al i.pedancebased assay avai.able from *** Mi.roarray data analysi. of CRC pati.nt samples showed a si.ni.i.ant down regulati.n of FFAR2 gene *** prompted us to study the FFAR2 i. ***,FFAR3 shares si.ni.i.ant structural and functi.nal homology wi.h FFAR2,we knocked down both these receptors i. CRC cell li.e HCT *** modi.i.d cell li.es exhi.i.ed hi.her proli.erati.n rate and were found to have i.creased glucose uptake as well as i.creased level of glucose transporter ***,FFAR2 and FFAR3 si.nal through G protei. subuni.(Gαi.,knockdown of these receptors was associ.ted wi.h i.creased *** of protei. ki.ase A(PKA)di. not alter the growth and proli.erati.n of these cells i.di.ati.g a mechani.m i.dependent of cAMP/PKA *** Our results suggest role of FFAR2/FFAR3 genes i. i.creased proli.erati.n of colon cancer cells vi. enhanced glucose uptake and exclude t

关键词： Cell proli.erati.n Glucose transporter 1 Colorectal cancer Free fatty aci.s receptor 2 Free fatty aci.s receptor 3 Glucose uptake

Hi.hli.hts i. pathogenesi. of vi.i.i.o

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World Journal of Cli.i.al Cases 2015年第3期3卷 221-230页

作者： Ghada F Mohammed amal Hussei. Gomaa Mohammed Saleh al-Dhubai.i Department of Dermatology and Venereology Faculty of Medicine Suez Canal University Department of Dermatology Faculty of Medicine Qassim University

Vi.i.i.o i. a common pi.mentary di.order. Many studi.s across decades and all over the world have attempted to i.lustrate the pathogenesi. behi.d i.; however, the pathogenesi. of vi.i.i.o remai.s elusi.e. Thi. revi.w arti.le, we present the fi.di.gs behi.d the most and updated theori.s behi.d thi. psychologi.ally debi.i.ati.g and di.fi.uri.g di.ease. The di.cussi.n begun wi.h the role of geneti. predi.posi.i.n followed by neural theory fi.st proposed i. the 1950 s. Wehi.hli.ht the autoi.mune hypothesi., followed by the reacti.e oxygen speci.s model, zi.c-α2-glycoprotei. defi.i.ncy hypothesi., vi.al theory, i.tri.si. theory and bi.chemi.al, molecular and cellular alterati.ns accounti.g for loss of functi.ni.g melanocytes i. vi.i.i.o. Many theori.s were elaborated to clari.y vi.i.i.o pathogenesi.. i. i. a multi.actori.l di.ease i.volvi.g the i.terplay of several factors. Future research i. needed to clari.y the i.teracti.n of these factors for better understandi.g of vi.i.i.o pathogenesi. and subsequent successful treatment.

关键词： Eti.pathogenesi. Pi.mentary di.order Non-segmental vi.i.i.o Segmental vi.i.i.o Vi.i.i.o

Opti.al Kernel Extreme Learni.g Machi.e for COVi.-19 Classi.i.ati.n on Epi.emi.logy Dataset

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Computers, Materi.ls & Conti.ua 2022年第11期73卷 3305-3318页

作者： Saud S.alotai.i.amal al-Rasheed Sami.althahabi.Manar Ahmed Hamza Abdullah Mohamed Abu Sarwar Zamani.Abdelwahed Motwakel Mohamed i.Eldesouki Department of i.formati.n Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of i.formati.n Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sci.nce College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Research Centre Future University in EgyptNew Cairo11745Egypt Department of i.formati.n System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Arti.i.i.l i.telli.ence(Ai.encompasses vari.us domai.s such as Machi.e Learni.g(ML),Deep Learni.g(DL),and other cogni.i.e technologi.s whi.h have been wi.ely appli.d i. healthcare *** models are uti.i.ed i. healthcare sector i. whi.h the machi.es are used to i.vesti.ate and make deci.i.ns based on predi.ti.n and classi.i.ati.n of i.put *** thi. moti.ati.n,the current study i.volves the desi.n of Metaheuri.ti. Opti.i.ati.n wi.h Kernel Extreme Learni.g Machi.e for COVi.-19 Predi.ti.n Model on Epi.emi.logy Dataset,named MOKELM-CPED *** pri.ary ai. of the presented MOKELM-CPED model i. to accompli.h effectual COVi.-19 classi.i.ati.n outcomes usi.g epi.emi.logy *** the proposed MOKELM-CPED model,the data fi.st undergoes pre-processi.g to transform the medi.al data i.to useful *** by,data classi.i.ati.n process i. performed by followi.g Kernel Extreme Learni.g Machi.e(KELM)***,Symbi.ti. Organi.m Search(SOS)opti.i.ati.n algori.hm i. uti.i.ed to fi.e tune the KELM parameters whi.h consequently helps i. achi.vi.g hi.h detecti.n *** order to i.vesti.ate the i.proved classi.i.r outcomes of MOKELM-CPED model i. an effectual manner,a comprehensi.e experi.ental analysi. was conducted and the results were i.spected under di.erse *** outcome of the experi.ents i.fer the enhanced performance of the proposed method over recent approaches under di.ti.ct measures.

关键词： COVi.-19 epi.emi.logy dataset machi.e learni.g arti.i.i.l i.telli.ence metaheuri.ti.s healthcare

Malassezi. Folli.uli.i. versus Truncal Acne Vulgari. (Cli.i.al and Hi.topathologi.al Study)

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Journal of Cosmeti.s, Dermatologi.al Sci.nces and Appli.ati.ns 2012年第4期2卷 277-282页

作者： Khali.a E. Sharqui. Khali. i. al-Hamdi.Sawsan S. al-haroon A. al-Mohammadi Chai.man of the Sci.nti.i. Counci. of Dermatology and Venereology Iraqi Board for Medical Specializations Department of Dermatology & Venereology Basrah Teaching Hospital Basra Iraq Head of Department of Dermatology & Venereology College of Medicine University of Basrah Basra Iraq Head of Department of Hi.topathology College of Medicine University of Basrah Basra Iraq

Background: Malassezi. folli.uli.i. i. an i.fecti.n of the hai. folli.le, whi.h commonly affects young adult, and i. often mi.di.gnosed as truncal acne. Objecti.es: To shed li.ht on di.ferent cli.i.al, hi.topathologi.al, and mi.robi.logi.al aspects of Malassezi. folli.uli.i. and to be compared wi.h truncal acne. Pati.nts and Methods: Thi. i. a descri.ti.e comparati.e cross secti.nal, out pati.nt based study, whi.h was conducted at the Department of Dermatology, Basrah Teachi.g Hospi.al from October 2008 to October 2009. Total number of 113 pati.nts wi.h papular and/or pustular folli.ular ski. lesi.ns on the trunk were enrolled i. thi. study. They were di.i.ed accordi.g to the cli.i.al features, Wood’s li.ht exami.ati.n, di.ect mi.roscopi. exami.ati.n, PAS stai.ed ski. bi.psy and the response to a tri.l of anti.ungal drugs i.to two groups: group 1: pati.nt wi.h Malassezi. folli.uli.i. and group 2: pati.nt wi.h truncal acne vulgari.. Results: Group 1: They were 53(46.9%) out of a total 113, 33(62.3%) males and 20(37.7%) females, thei. ages ranged from 19 - 40 years. Group 2 consi.ted of 60(53.1%) pati.nts, 25(41.6%) males and 35(58.4%) females, whose ages ranged from 14 - 29 years. The ages were earli.r i. the acne group i. compari.on wi.h MF group (p Malassezi. folli.uli.i. was more common among males than females, whi.e i. truncal acne, females predomi.ated males. The center of the back was the predomi.ant si.e among MF group affecti.g (90.6%) of pati.nts wi.h spari.g the face, i. contrast to truncal acne where the peri.hery of the back was i.volved i. (91.7%) and the face i. (75%) (p 0.0001). Wood’s li.ht exami.ati.n, ski. scrappi.g and PAS stai.ed ski. bi.psi.s were also posi.i.e i. all pati.nts wi.h MF i. contrast to acne group where all these tests were negati.e. all MF pati.nts showed marked response to a two weeks tri.l of anti.ungal whi.e the reverse i. true for the acne pati.nts, whereas the anti.i.ti. was the second most common leadi.g aggravati.g factor i.

关键词： Malassezi. Folli.uli.i. Basrah i.aq

Manta Ray Foragi.g Opti.i.ati.n wi.h Machi.e Learni.g Based Bi.medi.al Data Classi.i.ati.n

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Computers, Materi.ls & Conti.ua 2022年第11期73卷 3275-3290页

作者： amal al-Rasheed Jaber S.alzahrani.Majdy M.Eltahi. Abdullah Mohamed Anwer Mustafa Hi.al Abdelwahed Motwakel Abu Sarwar Zamani.Mohamed i.Eldesouki Department of i.formati.n Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of i.dustri.l Engi.eeri.g College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of i.formati.n Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of i.formati.n System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The bi.medi.al data classi.i.ati.n process has recei.ed si.ni.i.ant attenti.n i. recent ti.es due to a massi.e i.crease i. the generati.n of healthcare data from vari.us *** developments of arti.i.i.l i.telli.ence(Ai.and machi.e learni.g(ML)models assi.t i. the effectual desi.n of medi.al data classi.i.ati.n ***,thi. arti.le concentrates on the development of opti.al Stacked Long Short Term Memory Sequence-toSequence Autoencoder(OSAE-LSTM)model for bi.medi.al data *** presented OSAE-LSTM model i.tends to classi.y the bi.medi.al data for the exi.tence of ***,the OSAE-LSTM model i.volves mi.-max normali.ati.n based pre-processi.g to scale the data i.to uni.orm *** by,the SAE-LSTM model i. uti.i.ed for the detecti.n and classi.i.ati.n of di.eases i. bi.medi.al *** last,manta ray foragi.g opti.i.ati.n(MRFO)algori.hm has been employed for hyperparameter opti.i.ati.n *** uti.i.ati.n of MRFO algori.hm assi.ts i. opti.al selecti.n of hypermeters i.volved i. the SAE-LSTM *** si.ulati.n analysi. of the OSAE-LSTM model has been tested usi.g a set of benchmark medi.al datasets and the results reported the i.provements of the OSAELSTM model over the other approaches under several di.ensi.ns.

关键词： Bi.medi.al data classi.i.ati.n deep learni.g manta ray foragi.g opti.i.ati.n healthcare machi.e learni.g arti.i.i.l i.telli.ence