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A New Optimized Wrapper Gene Selection Method for Breast Cancer Prediction

Computers, Materials & Continua 2021年第6期67卷 3089-3106页

作者： heyam h.al-baity Nourah.al-Mutlaq Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

Machine-learning algorithms have been widely used in breast cancer diagnosis to help pathologists and physicians in the decision-making ***,the high dimensionality of genetic data makes the classification process a challenging *** this paper,we propose a new optimized wrapper gene selection method that is based on a nature-inspired algorithm(simulated annealing(SA)),which will help select the most informative genes for breast cancer *** optimal genes will then be used to train the classifier to improve its accuracy and *** supervised machine-learning algorithms,namely,the support vector machine,the decision tree,and the random forest were used to create the classifier models that will help to predict breast *** different experiments were conducted using three datasets:Gene expression(GE),deoxyribonucleic acid(DNA)methylation,and a combination of the *** measures were used to evaluate the performance of the proposed algorithm,which include the following:Accuracy,precision,recall,specificity,area under the curve(AUC),and execution *** effectiveness of the proposed classifiers was evaluated through comprehensive *** results demonstrated that our approach outperformed the conventional classifiers as expected in terms of accuracy and execution *** accuracy values of 99.77%,99.45%,and 99.45%have been achieved by SA-SVM for GE,DNA methylation,and the combined datasets,*** execution time of the proposed approach was significantly reduced,in comparison to that of the traditional classifiers and the best execution time has been reached by SA-SVM,which was 0.02,0.03,and 0.02 on GE,DNA methylation,and the combined datasets *** regard to precision and specificity,SA-RF obtained the best result of 100 on GE *** SA-SVM attained the best recall result of 100 on GE dataset.

关键词： Breast cancer simulated annealing feature selection classification gene expression DNA methylation DNA microarray

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Machine Learning Approach for COVID-19 Detection on Twitter

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Computers, Materials & Continua 2021年第8期68卷 2231-2247页

作者： Samina Amin M.Irfan Uddin heyam h.al-baity M.ali Zeb M.Abrar Khan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

Social networking services(SNSs)provide massive data that can be a very influential source of information during pandemic *** study shows that social media analysis can be used as a crisis detector(e.g.,understanding the sentiment of social media users regarding various pandemic outbreaks).The novel Coronavirus Disease-19(COVID-19),commonly known as coronavirus,has affected everyone worldwide in *** Twitter data have revealed the status of the COVID-19 outbreak in the most affected *** study focuses on identifying COVID-19 patients using tweets without requiring medical records to find the COVID-19 pandemic in Twitter messages(tweets).For this purpose,we propose herein an intelligent model using traditional machine learning-based approaches,such as support vector machine(SVM),logistic regression(LR),naïve Bayes(NB),random forest(RF),and decision tree(DT)with the help of the term frequency inverse document frequency(TF-IDF)to detect the COVID-19 pandemic in Twitter *** proposed intelligent traditional machine learning-based model classifies Twitter messages into four categories,namely,confirmed deaths,recovered,and *** the experimental analysis,the tweet data on the COVID-19 pandemic are analyzed to evaluate the results of traditional machine learning approaches.A benchmark dataset for COVID-19 on Twitter messages is developed and can be used for future research *** experiments show that the results of the proposed approach are promising in detecting the COVID-19 pandemic in Twitter messages with overall accuracy,precision,recall,and F1 score between 70%and 80%and the confusion matrix for machine learning approaches(i.e.,SVM,NB,LR,RF,and DT)with the TF-IDF feature extraction technique.

关键词： Artificial intelligence coronavirus COVID-19 pandemic social network Twitter machine learning natural language processing

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Dart Games Optimizer with Deep Learning-Based Computational Linguistics Named Entity Recognition

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Intelligent Automation & Soft Computing 2023年第9期37卷 2549-2566页

作者： Mesfer al Duhayyim hala J.alshahrani Khaled Tarmissi heyam h.al-baity Abdullah Mohamed Ishfaq Yaseen Amgad Atta Abdelmageed Mohamed IEldesouki Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl Aflaj16828Saudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityP.O.Box 145111Riyadh4545Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Computational linguistics is an engineering-based scientific *** deals with understanding written and spoken language from a computational ***,the domain also helps construct the artefacts that are useful in processing and producing a language either in bulk or in a dialogue *** Entity Recognition(NER)is a fundamental task in the data extraction *** concentrates on identifying and labelling the atomic components from several texts grouped under different entities,such as organizations,people,places,and ***,the NER mechanism identifies and removes more types of entities as per the *** significance of the NER mechanism has been well-established in Natural Language Processing(NLP)tasks,and various research investigations have been conducted to develop novel NER *** conventional ways of managing the tasks range from rule-related and hand-crafted feature-related Machine Learning(ML)techniques to Deep Learning(DL)*** this aspect,the current study introduces a novel Dart Games Optimizer with hybrid Deep Learning-Driven Computational Linguistics(DGOhDL-CL)model for *** presented DGOhDL-CL technique aims to determine and label the atomic components from several texts as a collection of the named *** the presented DGOhDL-CL technique,the word embed-ding process is executed at the initial stage with the help of the word2vec *** the NER mechanism,the Convolutional Gated Recurrent Unit(CGRU)model is employed in this *** last,the DGO technique is used as a hyperparameter tuning strategy for the CGRU algorithm to boost the NER’s *** earlier studies integrated the DGO mechanism with the CGRU model for *** exhibit the superiority of the proposed DGOhDL-CL technique,a widespread simulation analysis was executed on two datasets,CoNLL-2003 and OntoNotes *** experimental outcomes establish the promising performance of the DGOhDL-CL technique over other models.

关键词： Named entity recognition deep learning natural language processing computational linguistics dart games optimizer

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Insights into the anorexic mechanism of Khat:an integrated in vivo,ex vivo,and in silico investigations

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Traditional Medicine Research 2024年第10期9卷 36-51页

作者： Ahmed ali Jerah Manal Mohamed Elhassan Taha Abdullah Farasani Sivakumar Sivagurunathan Moni Emad Sayed Shaheen Andleeb Khan Ibrahim Abdo Khardali Magbool Oraiby heyam Mohamed ali Sidahmed Siddig Ibrahim Abdelwahab Department of Medical Laboratory Technology College of Applied Medical SciencesJazan UniversityJazan 45142Saudi Arabia h.alth Research Centre Jazan UniversityJazan 45142Saudi Arabia Department of Pharmaceutics College of PharmacyJazan UniversityJazan 45142Saudi Arabia Department of Biosciences Faculty of ScienceIntegral UniversityLucknow 226026India Poison Control and Medical Forensic Chemistry Center General Directorate of Health AffairsJazan 45142Saudi Arabia Department of Pharmaceutical Chemistry Faculty of PharmacyAl-Neelain UniversityKhartoum 16458Sudan

Background:Chewing Khat(Catha edulis)releases cathine and cathinone,which may reduce appetite via an unknown *** study investigated the peripheral and central effects of fresh leaves and buds of Catha edulis water extract(CEWE)on appetite biomarkers,gene expression,and body weight,using in vivo,ex vivo,and in silico ***:Rats of both sexes were orally administered CEWE at different doses and durations in three different *** chromatography-mass spectroscopy(LC-MS)-MS was used to detect cathinone and cathine in the murine *** effect of Khat on serotonin receptors was studied in isolated rat fundus *** of the two Khat ligands was performed on G(The 5-hydroxytryptamine-type 2C receptor(5-hT2C)in an agonist-bound active conformation)and h(5-hT2C in an antagonist-bound inactive conformation)proteins to determine which ligands are most likely to act as agonists or ***:Significant differences(Pht were observed between the CEWE-treated groups and the controls over eight ***,the plasma leptin and ghrelin levels did not change significantly(P>0.05).The expression of the ghrelin and leptin genes was also unaffected,but the expression of the 5-hydroxytryptamine(5-hT)gene decreased(Ph CEWE *** antagonizes 5-hT receptors in isolated rat fundus *** findings indicated that the khat ligands bound to 5-hT2C *** and cathinone levels in rat plasma were ***:Khat extract may suppress appetite by antagonizing the 5-hT *** research is required to understand its mechanism and potential applications.

关键词： Catha edulis appetite leptin ghrelin 5-hydroxytryptamine molecular docking

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Evaluating Agile Practices for Reducing Cost Overruns in Yemen's Construction Projects

Evaluating Agile Practices for Reducing Cost Overruns in Yem...

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作者： heyam Mohammed ali Mughir 山东大学

学位级别：硕士

也门建筑项目的成本超支已成为一种普遍现象,不可避免地导致拖延、法律索赔,有时甚至导致项目失败。随着项目变得越来越复杂,超出预算的情况也越来越难以预料。大多数企业倾向于采用最好最新的技术、新的管理理念和哲学来实现项目成本... 详细信息

也门建筑项目的成本超支已成为一种普遍现象,不可避免地导致拖延、法律索赔,有时甚至导致项目失败。随着项目变得越来越复杂,超出预算的情况也越来越难以预料。大多数企业倾向于采用最好最新的技术、新的管理理念和哲学来实现项目成本超支的改进。本研究的最初动机是探索一种灵活的方法来处理也门建设项目的成本超支,同时,提高项目的整体性能。本文首先讨论了也门建筑施工成本超支的问题。然后在敏捷施工的概念模型下提出敏捷实践,以解决当前成本估算不准确、变更订单、劳动生产率低等成本问题。敏捷管理,源自敏捷理论在其他工程领域的应用,是一种集成的策略,通过在项目生命周期中应用敏捷方法,使项目能够在灵活的环境中茁壮成长。通过(AhP)方法,由施工专业人员对提出的敏捷实践进行评估。研究发现,采用敏捷实践将有助于建筑项目减少成本超支,并提高其性能。本文提出了一些建议,以帮助也门的建筑项目经理从敏捷管理中获益。

关键词：敏捷管理建设项目成本超支也门 (AhP)方法

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The Impact of Coronavirus on Staff Nurses’ Feeling While Giving Direct Care to COVID-19 Patients in Various COVID Facilities

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Open Journal of Nursing 2020年第9期10卷 873-889页

作者： Sanaa M. Taghaddom heyam M. A. R. B. alrashidi hoda Diab Mohamed Marthal Nandhini Johnson Nursing Services Administration Kuwait City Kuwait Mubarak al Kabeer hospital Jabriya Kuwait

Background: Nurses are very important frontline h.alth care professionals as they spend more time with patients than other professionals. This is even more so at this critical time of the COVID-19 pandemic. The nursing profession is facing great challenges in coping with the pandemic as they are more vulnerable to exposure and infection with the disease. Kuwait is not spared from the global pandemic which has put the h.alth sector under immense pressure. Because COVID-19 is highly transmissible and deadly, it poses a huge h.alth risk to nurses and has a huge impact on their cognitive, emotional, behavioural and physical dimensions. Aim: The study aims to explore the positive and negative emotions and feelings of staff nurses while giving care to COVID-19 patients. Materials and Methods: A descriptive cross-sectional study was carried out. 300 nurses from different general hospitals, field hospitals, and quarantine facilities in Kuwait participated in the study. A questionnaire was used to collect the data. Results: The findings show that for the cognitive evaluation, 72% were moderately affected, for the emotional evaluation 51.3% and 44% were moderately and mildly affected respectively, for the behavioural evaluation, 66.7% were severely affected, and for the physical evaluation, 43.3% and 31.7% were moderately and severely affected respectively. Prolonged working hours has a highly significant negative correlation to emotional (r −0.165), behavioral (r −0.177) and physical (r −0.155) dimension of the nurses at 0.01 level using Spearman’s correlation. Conclusion: The study concluded that the COVID-19 pandemic has affected the psychophysical dimensions of staff nurses.

关键词： COVID-19 Pandemic Psychophysical Dimensions Positive and Negative Emotions Positive and Negative Feeling Field hospital Quarantine Facility

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性别视角与博物馆：性别作为诠释展览的工具

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美术馆 2020年第2期 8-8页

作者： James Daybell Kit heyam Svant e Norrhem Emma Severinsson

无论对于个人还是社区,博物馆都是可以持续一生的学习和修身养性的场所。而对博物馆来说,这意味着它有义务保证自身叙事的多元化,这种多元化对性别议题来说尤其如是。然而事实却是,虽然很多博物馆意识到性别在策展和释展中的重要性,它...

无论对于个人还是社区,博物馆都是可以持续一生的学习和修身养性的场所。而对博物馆来说,这意味着它有义务保证自身叙事的多元化,这种多元化对性别议题来说尤其如是。然而事实却是,虽然很多博物馆意识到性别在策展和释展中的重要性,它们依然不知道应该如何在具体操作上展现藏品背后的性别历史。鉴于此,来自英国普利茅斯大学、瑞典隆德大学、荷兰莱登大学、西澳大学和V&A博物馆等机构的研究人员进行了为时两年的博物馆性别诠释研究,

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