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Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification

Computers, Materials & Continua 2022年第8期72卷 2859-2875页

作者： Areej A.Malibari Siwar Ben Haj Hassine Abdelwahed Motwakel Manar ahmed Hamza Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayilAsirSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Atherosclerosis diagnosis is an inarticulate and complicated cognitive *** on medical diagnosis necessitate maximum accuracy and performance to make optimal clinical *** the medical diagnostic outcomes need to be prompt and accurate,the recently developed artificial intelligence(AI)and deep learning(DL)models have received considerable attention among research *** study develops a novel Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification(MDL-BADDC)*** proposed MDL-BADDC technique encompasses several stages of operations such as pre-processing,feature selection,classification,and parameter ***,the proposed MDL-BADDC technique designs a novel Quasi-Oppositional Barnacles Mating Optimizer(QOBMO)based feature selection ***,the deep stacked autoencoder(DSAE)based classification model is designed for the detection and classification of atherosclerosis ***,the krill herd algorithm(KHA)based parameter tuning technique is applied to properly adjust the parameter *** order to showcase the enhanced classification performance of the MDL-BADDC technique,a wide range of simulations take place on three benchmarks biomedical *** comparative result analysis reported the better performance of the MDL-BADDC technique over the compared methods.

关键词： Atherosclerosis disease biomedical data data classification machine learning disease diagnosis deep learning

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Enhanced Object Detection and Classification via Multi-Method Fusion

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Computers, Materials & Continua 2024年第5期79卷 3315-3331页

作者： Muhammad Waqas ahmed Nouf Abdullah Almujally Abdulwahab Alazeb Asaad Algarni Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073South Korea

Advances in machine vision systems have revolutionized applications such as autonomous driving,robotic navigation,and augmented *** substantial progress,challenges persist,including dynamic backgrounds,occlusion,and limited labeled *** address these challenges,we introduce a comprehensive methodology toenhance image classification and object detection *** proposed approach involves the integration ofmultiple methods in a complementary *** process commences with the application of Gaussian filters tomitigate the impact of noise *** images are then processed for segmentation using Fuzzy C-Meanssegmentation in parallel with saliency mapping techniques to find the most prominent *** Binary RobustIndependent Elementary Features(BRIEF)characteristics are then extracted fromdata derived fromsaliency mapsand segmented *** precise object separation,Oriented FAST and Rotated BRIEF(ORB)algorithms *** Algorithms(GAs)are used to optimize Random Forest classifier parameters which lead toimproved *** method stands out due to its comprehensive approach,adeptly addressing challengessuch as changing backdrops,occlusion,and limited labeled data concurrently.A significant enhancement hasbeen achieved by integrating Genetic Algorithms(GAs)to precisely optimize *** minor adjustmentnot only boosts the uniqueness of our system but also amplifies its overall *** proposed methodologyhas demonstrated notable classification accuracies of 90.9%and 89.0%on the challenging Corel-1k and MSRCdatasets,***,detection accuracies of 87.2%and 86.6%have been *** ourmethod performed well in both datasets it may face difficulties in real-world data especially where datasets havehighly complex *** these limitations,GAintegration for parameter optimization shows a notablestrength in enhancing the overall adaptability and performance of our system.

关键词： BRIEF features saliency map fuzzy c-means object detection object recognition

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Factors affecting improvement of fluorescence intensity of quartet and doublet state of NO diatomic molecule excited by glow discharge

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Chinese Physics B 2018年第8期27卷 356-363页

作者： ahmed Asaad I Khalilt Reem A1-Tuwirqi Mohamed Gondal Noura A1-Suliman Department of Laser Sciences and Interactions National Institute of Laser Enhanced Sciences(NILES)Cairo UniversityGiza12613 Egypt Department of Physics Faculty of ScienceKing Abdulaziz UniversityJeddah 21551Saudi Arabia Department of Physics King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia Department of Physics Faculty of Science for GirlsImam Abdulrahman Ben Faisal UniversityDammam 31441Saudi Arabia

We report on the observation of new fluorescence emission spectral transitions obtained from NO diatomic molecule in the region from ultraviolet （UV） to near infrared （NIR） in a low power glow discharge system. This glow discharge electronic excitation populates different quartet and doublet states of NO in its proximity such as the A2Z （/9 = 2）, b4∑- （υ= 3）, B2М （1） = 4）, and X2Л （u= 33-32） states. Due to inter-system crossing, emission lines originating from these levels to lower lying states are recorded and spectral line assignments are performed. The observed systems include b4∑- a4∏, B21∏-a4∏, a4∏-X2I∏, A2∑X2∏, X2∏-X2∏ （33-15）, X2∏-X2∏ （33-17）, X2∏-X2∏ （33-20）, and X2∏-X2∏ （33- 18）. This new information will conduce to the better understanding of the interesting features of NO molecule. Such parameters that affect the recording of low density of NO molecules are also discussed In addition to the factors such as the time evolution, argon gas concentration relative to NO mixture, the percentage of NO molecular gas concentration, discharge electric current signals and discharge applied voltage are studied. Those factors would enhance the fluorescence signal intensity of NO molecules. The recent results might be significant as reference data for optimizing the glow discharge spectrometer and diagnostics of NO gas.

关键词： fluorescence emission NO molecule quartet states intersystem crossing glow discharge

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Efficacy and safety of treatment of hepatitis C virus infection in renal transplant recipients

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World Journal of Gastroenterology 2012年第1期18卷 55-63页

作者： abdulrahman A Aljumah Mohamed A Saeed ahmed I Al Flaiw Ibrahim H Al Traif Abduljaleel M Al Alwan Salem H Al Qurashi Ghormallah A Al Ghamdi Fayez F Al Hejaili Mohammed A Al Balwi Abdulla A Al Sayyari Division of Hepatology Department of Hepatobiliary Sciences and Liver Transplantation King Abdulaziz Medical City and King Saud bin Abdulaziz University for Health Sciences National Guard Health Affairs Division of Nephrology and Renal Transplantation Department of Medicine King Abdulaziz Medical City and King Saud bin Abdulaziz University for Health Sciences National Guard Health Affairs Division of Molecular Pathology and Genetics King Abdulaziz Medical City and King Saud bin Abdulaziz University for Health Sciences National Guard Health Affairs

AIM: To assess the efficacy and safety of combinedpegylated interferon and ribavirin therapy in hepatitis C virus (HCV) infection in renal transplant recipients. METHODS: This is a retrospective chart review of post renal transplant patients who were positive for anti-HCV and HCV-RNA, and who have received treatment with combination of pegylated interferon and ribavirin between October 2003 and December 2008. Only patients with stable graft function and absence of evidence of cirrhosis and who received the therapy for continuous 48 wk were included. Nineteen patients (13 male and 6 female) were identified and included. The patient's complete blood count, liver and kidney prof ile, and cal- culated glomerular f iltration rate (GFR) were monitored every 6-8 wk while on treatment. HCV-RNA was tested at 12 wk for early virological response, at 48 wk for end of treatment response (ETR), and then retested at 24, and 48 wk after completion of therapy for sustained virological response (SVR). Liver biopsies were obtained before treatment from all patients and graft kidney biopsies were performed as required. RESULTS: Of the entire cohort, 9 patients (47.4%) showed an ETR and 8 had SVR (42.1%). Of the 8 patients with abnormal alanine aminotransferase (ALT) levels at baseline, 78.9% had their ALT normalized (including the virological non responders). ALT was normal in all responders at the end of therapy and at 24 wk post therapy (100%). Only one patient (5.3%) developed an increase in creatinine and decline in GFR from baseline towards the end of treatment. This patient's kidney biopsy revealed borderline rejection. There was no impact on response by HCV-genotype, initial HCV RNA load, age or sex of the patient or duration post transplant before commencement of therapy. All patients tolerated treatment in the same way as non-transplant with no unusual or increased occurrence of side effects. CONCLUSION: The combination of pegylated interferon and ribavirin is effective in su

关键词： Allograft rejection Hepatitis C Pegylated interferon Ribavirin Renal transplant

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Aconite Poisoning with Good Outcome, Case Study and Literature Review

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Case Reports in Clinical Medicine 2020年第8期9卷 217-222页

作者： abdulrahman Alalmay Ali Al Bashabshe Nouf Al Shamrani Lujain Bin Othman Musa Alfaifi Yahya Algarni ahmed Awwadh Ali Alhanash Hassan Ogran Khalid Sinnah Mostafa El Razzaz King Khaled University Abha KSA Ministry of Health Abha KSA Internal Medicine Ain Shams University Cairo Egypt

Aconite poisoning has been reported in previously published literature and case reports. It may occur due to accidental consumption of aconite tubers or when it is used in medicinal preparations. In this case report we describe a case of aconite poisoning in a primary case of anxiety disorder, after use of herbal medicine. He gave history of consumption of herbal remedy with honey from folk medicine with unknown content. Our patient presented with symptoms of vomiting, diarrhea, numbness and dizziness that are common symptoms of aconite poisoning. The management was mainly supportive care depending on the symptoms. Our patient recovered after 30 hours, probably due to slow elimination of the metabolites overtime. Our case represents one case where poisoning was not due to wrong consumption but due to drug-drug interaction. It is important that physicians should take drug interactions into consideration while prescribing drugs and also educate patients regarding the same.

关键词： Aconite Herbal Medications Poisoning Anxiety Disorder

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An Optimized Algorithm for CR-MIMO Wireless Networks

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Computers, Materials & Continua 2022年第4期71卷 697-715页

作者： Imran Khan Fahd N.Al-Wesabi Marwa Obayya Anwer Mustafa Hilal Manar ahmed Hamza Mohammed Rizwanullah Fahad ahmed Al-Zahrani Hirofumi Amano Samih M.Mostafa Department of Electrical Engineering University of Engineering&TechnologyPeshawarPakistan Department of Computer Science King Khalid UniversityMuhayel AseerKSA Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Computer Engineering Department Umm Al-Qura UniversityMecca24381Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

With the rapid development of wireless communication technology,the spectrum resources are increasingly strained which needs optimal *** radio(CR)is one of the key technologies to solve this *** sensing not only includes the precise detection of the communication signal of the primary user(PU),but also the precise identification of its modulation type,which can then determine the a priori information such as the PU’service category,so as to use this information to make the cognitive user(CU)aware to discover and use the idle spectrum more effectively,and improve the spectrum *** sensing is the primary feature and core part of *** sensing algorithms includes energy detection,cyclostationary feature detection,matched filter detection,and so *** energy detection algorithm has a simple structure and does not require prior knowledge of the PU transmitter signal,but it is easily affected by noise and the threshold is not easy to *** combination of multiple-input multiple-output(MIMO)with CR improves the spectral efficiency and multipath fading *** best utilize the PU spectrum while minimizing the overall transmit power,an iterative technique based on semidefinite programming(SDP)and minimum mean squared error(MMSE)is ***,this article proposed a new method for max-min fairness *** compared to existing algorithms,the simulation results show that the proposed algorithms perform better in terms of total transmitted power and signal-tointerference plus noise ratio(SINR).Furthermore,the proposed algorithm effectively improved the system performance in terms of number of iterations,interference temperature threshold and balance SINR level which makes it superior over the conventional schemes.

关键词： Cognitive radio spectrum utilization bandwidth primary user

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Sunitinib Reduces Acute Myeloid Leukemia Clonogenic Cells in Vitro and Has Potent Inhibitory Effect on Sorted AML ALDH+ Cells

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Open Journal of Blood Diseases 2016年第1期6卷 9-16页

作者： Asad M. Ilyas Youssri ahmed Mamdooh Gari Mohammed H. Alqahtani Taha A. Kumosani abdulrahman L. Al-Malki Khalid O. Abualnaja Saad H. S. Albohairi Adeel G. A. Chaudhary Farid ahmed Centre of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Department of Biochemistry Faculty of Science King Abdulaziz University Jeddah Saudi Arabia Production of Bioproducts for Industrial Applications Research Group Experimental Biochemistry Unit King Fahd Medical Research Center King Abdulaziz University Jeddah Saudi Arabia Microbial Biotechnology Department National Research Center Cairo Egypt Bioactive Natural Products Research Group Experimental Biochemistry Unit King Fahd Medical Research Center King Abdulaziz University Jeddah Saudi Arabia King Abdulaziz University Hospital Jeddah Saudi Arabia

Sunitinib is an orally administered, multi-target tyrosine kinase inhibitor that has been approved by the FDA for the treatment of renal cell carcinoma and imatinib resistant gastro-intestinal tumors. Anti-leukemic activity of sunitinib has been examined in early clinical trials with limited success. However, recent trials on acute myeloid leukemia (AML) patients carrying FLT3 mutations have shown promising results. Effects of sunitinib on leukemic clonogenic cells and potential leukemic stem cells have not been examined so far. We analyzed the anti-proliferative and apoptotic properties of sunitinib on AML-derived cell lines. We also tested the effect of sunitinib on AML patient derived clonogenic cells (AML-CFC), as well as flow-sorted potential leukemic progenitors. Peripheral blood or bone marrow samples were obtained from newly diagnosed AML patients and flow sorted for CD34+ CD133+ or ALDH+ cells. Umbilical cord blood derived CD34+ cells were used as normal controls. Sunitinib induced growth arrest and apoptosis in AML derived cell lines. In addition, 7 μM sunitinib induced 75% reduction of AML-CFC as compared to DMSO treated control (±6.79%;n = 4). In contrast, 7 μM sunitinib treatment of umbilical cord blood derived normal CD34+ cells showed 29% reduction in AML-CFC (±6.77%;n = 5). Treatment of ALDH+ cells sorted from 2 AML cases and CD34+ CD133+ cells from one patient showed reduction of AML-CFC on treatment with sunitinib. Our study highlighted a potent anti-proliferative and proapoptotic effect of sunitinib on AML cell lines, AML patient derived clonogenic cells and potential leukemic stem cells.

关键词： Acute Myeloid Leukemia Sunitinib Tyrosine Kinase Inhibitor AML-CFC Leukemic Stem Cells

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Toxic and Antifeedant Effects of Different Pesticidal Plant Extracts against Beet Armyworm (Spodoptera exigua)

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Phyton-International Journal of Experimental Botany 2023年第4期92卷 1161-1172页

作者： Muhammad Asad Rashad Rasool Khan ahmed B.Aljuboory Muhammad Haroon URashid Uttam Kumar Inzamam Ul Haq Aqsa Hafeez ahmed Noureldeen Khadiga Alharbi College of Life Science Fujian Agriculture and Forestry UniversityFuzhou350002China Department of Entomology University of AgricultureFaisalabad38000Pakistan Department of Plant Protection College of Agricultural Engineering ScienceUniversity of BaghdadBaghdad10071Iraq Department of Forestry and Range Management University of AgricultureFaisalabad38000Pakistan College of Plant Protection Fujian Agriculture and Forestry University Fuzhou350002China College of Plant Protection Gansu Agricultural UniversityLanzhou730070China Department of Plant Sciences Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Biology College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Biology College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The beet armyworm(BAW),Spodoptera exigua(Lepidoptera:Noctuidae)is a highly destructive pest of vegetables and field *** of beet armyworm primarily relies on synthetic pesticides,which is threatening the beneficial community and *** importantly,the BAW developed resistance to synthetic pesticides with making it difficult to ***,alternative and environment-friendly pest management tactics are urgently *** use of pesticidal plant extracts provides an effective way for a sustainable pest management *** evaluate the use of pesticidal plant extracts against BAW,we selected six plant species(Lantana camara,Aloe vera,Azadirachta indica,Cymbopogon citratus,Nicotiana tabacum,and Ocimum basilicum)for initial screening *** out of six plant species such as ***,***,*** and *** showed promising mortality of more than 50%.Therefore,we selected these four plant extracts for the subsequent *** contact bioassay,*** showed high mortality 66.63%,followed by the *** 53.33%,at 10%w/v ***,*** showed the highest mortality rate,66%at 10%w/v concentration,followed by the *** 46%through feeding ***,the feeding deterrence assay showed that *** had a high antifeedant index(−50)followed by ***(−39),and ***(−28).In living plant assay,the *** extract showed a low mean damage score 3.6 on living cotton plant followed by *** 4.5 and *** ***,extracts of three plant species provided promising results against the BAW,which can minimize the use of synthetic chemicals,particularly for small landholding *** studies are also required to evaluate the effects of these plant extract against BAW on cotton plants under field conditions to optimize the further use.

关键词： Bioassay methods feeding deterrence botanical pesticide pest management sustainable agriculture

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A Novel Metadata Based Multi-Label Document Classification Technique

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Computer Systems Science & Engineering 2023年第8期46卷 2195-2214页

作者： Naseer ahmed Sajid Munir Ahmad Atta-ur Rahman Gohar Zaman Mohammed Salih ahmed Nehad Ibrahim Mohammed Imran Bahmed Gomathi Krishnasamy Reem Alzaher Mariam Alkharraa Dania AlKhulaifi Maryam AlQahtani Asiya A.Salam Linah Saraireh Mohammed Gollapalli Rashad ahmed Barani Institute of Information Technology(BIIT) PMAS Arid Agriculture UniversityRawalpindi46000PunjabPakistan Department of Computer Science(CS) College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Faculty Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaBatu PahatMalaysia Department of Computer Engineering(CE) College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia College of Business Administration Imam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Information System(CIS) College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia ICS Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

From the beginning,the process of research and its publication is an ever-growing phenomenon and with the emergence of web technologies,its growth rate is *** a rough estimate,more than thirty thousand research journals have been issuing around four million papers annually on *** engines,indexing services,and digital libraries have been searching for such publications over the ***,getting the most relevant articles against the user requests is yet a *** is mainly because the articles are not appropriately indexed based on the hierarchies of granular subject *** overcome this issue,researchers are striving to investigate new techniques for the classification of the research articles especially,when the complete article text is not available(a case of nonopen access articles).The proposed study aims to investigate the multilabel classification over the available metadata in the best possible way and to assess,“to what extent metadata-based features can perform in contrast to content-based approaches.”In this regard,novel techniques for investigating multilabel classification have been proposed,developed,and evaluated on metadata such as the Title and Keywords of the *** proposed technique has been assessed for two diverse datasets,namely,from the Journal of universal computer science(***)and the benchmark dataset comprises of the articles published by the Association for computing machinery(ACM).The proposed technique yields encouraging results in contrast to the state-ofthe-art techniques in the literature.

关键词： Multilabel classification indexing metadata content/data mining

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A Novel Cryptocurrency Prediction Method Using Optimum CNN

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Computers, Materials & Continua 2022年第4期71卷 1051-1063页

作者： Syed H.Hasan Syeda Huyam Hasan Mohammed Salih ahmed Syed Hamid Hasan Iowa State University AmesUSA University of Texas at Arlington USA Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

In recent years,cryptocurrency has become gradually more significant in economic regions *** cryptocurrencies,records are stored using a cryptographic *** main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social *** is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media ***,this work focuses on extracting Tweets and gathering data from different sources to classify them into positive,negative,and neutral categories,and further examining the correlations between cryptocurrency movements and Tweet *** paper proposes an optimized method using a deep learning algorithm and convolution neural network for cryptocurrency prediction;this method is used to predict the prices of four cryptocurrencies,namely,Litecoin,Monero,Bitcoin,and *** results of analyses demonstrate that the proposed method forecasts prices with a high accuracy of about 98.75%.The method is validated by comparison with existing methods using visualization tools.

关键词： Cryptocurrency litecoin monero bitcoin ethereum twitter optimal CNN price prediction sentiment analysis

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