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Seasonal electric vehicle forecasting model based on machine learning and deep learning techniques

Energy and AI 2023年第4期14卷 398-414页

作者： heba-Allah I.El-Azab R.A.Swief Noha H.El-Amary H.K.Temraz Faculty of Engineering Ahram Canadian University(ACU)GizaEgypt Faculty of Engineering Ain Shams UniversityCairo 11517Egypt Arab Academy for Science Technology and Maritime Transport(AASTMT)Cairo 2033Egypt

In this paper,multiple featured machine learning algorithms and deep learning algorithms are applied in fore-casting the electric vehicles charging load profile from real datasets of Spain’s electrical *** study aims to provide realistic datasets of electric vehicle load profiles to cope with the potential increase in electric vehicle penetration taking into consideration the seasonality *** issues are caused by the distribution network of the electricity grid;such as the huge charging power and stochastic charging behaviors of the drivers of electric vehicles due to the mass rollout of electric *** electric vehicles’load profile is necessary to face challenges to solve the problem of the potential mass rollout of electric vehicles ***,Electric vehicle is considered one of the most promising solutions that develops faster than other stochastic renewable solution to reduce greenhouse *** seasonality effect is one of the huge chal-lenges on electrical loads,so it is investigated by creating four separate forecasting networks to increase system accuracy and studying the effect of seasonal factors such as temperature fluctuation in the four seasons affecting the electric vehicles’battery in charging and draining *** factors are affecting the accuracy of the forecasting *** featured algorithms are *** Neural Networks and Adaptive Neuro-Fuzzy Inference Systems are applied as machine learning algorithms,and Long Short-Term Memory and the Gated Recurrent Units are also utilized as deep learning *** Gated Recurrent Units model performs slightly better than the long short-term memory employed on the hourly average daily historical data of charging electric *** the Adaptive Neuro-Fuzzy Inference System gathers both Artificial Neural Network and Fuzzy Inference System advantages.

关键词： Adaptive neuro-fuzzy inference system Deep learning Electric vehicles Gated recurrent units Long short-term memory Neural network Short-term load forecasting

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Automated Autism Spectral Disorder Classification Using Optimal Machine Learning Model

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Computers, Materials & Continua 2023年第3期74卷 5251-5265页

作者： hanan Abdullah Mengash hamed Alqahtani Mohammed Maray Mohamed K.Nour Radwa Marzouk Mohammed Abdullah Al-hagery heba Mohsen Mesfer Al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial Intelligence and Unit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Autism Spectrum Disorder (ASD) refers to a neuro-disorder wherean individual has long-lasting effects on communication and interaction *** information technologywhich employs artificial intelligence(AI) model has assisted in early identify ASD by using pattern *** advances of AI models assist in the automated identification andclassification of ASD, which helps to reduce the severity of the *** study introduces an automated ASD classification using owl searchalgorithm with machine learning (ASDC-OSAML) model. The proposedASDC-OSAML model majorly focuses on the identification and classificationof ASD. To attain this, the presentedASDC-OSAML model follows minmaxnormalization approach as a pre-processing stage. Next, the owl searchalgorithm (OSA)-based feature selection (OSA-FS) model is used to derivefeature subsets. Then, beetle swarm antenna search (BSAS) algorithm withIterative Dichotomiser 3 (ID3) classification method was implied for ASDdetection and classification. The design of BSAS algorithm helps to determinethe parameter values of the ID3 classifier. The performance analysis of theASDC-OSAML model is performed using benchmark dataset. An extensivecomparison study highlighted the supremacy of the ASDC-OSAML modelover recent state of art approaches.

关键词： Autism spectral disorder machine learning owl search algorithm feature selection id3 classifier

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Synthesis and spectroscopic characterization of novel 2-amino-4,5,6,7-tetrahydro-3H-cyclopenta[d]pyrimidine and pyrimido[1,2-α]pyrimidine derivatives

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Chinese Chemical Letters 2015年第6期26卷 690-694页

作者： Mohamed S.A.El-Gaby Jehan A.Micky Nadia M.Saleh Yousry A.Ammar heba S.A.Mohamed Chemistry Department Faculty of ScienceAl-Azhar University at Assiut Chemistry Department Faculty of Science (Girl’s)Al-Azhar University Chemistry Department Faculty of ScienceAl-Azhar University Photochemistry Department National Research CenterEl-DokkiGizaEgypt

2-Aminocyclopenta[d]pyrimidines 3a-c were achieved via a one-pot, three-component reactions of cyclopentanone 1, aromatic aldehyde and guanidine hydrochloride （1：2：1 molar ratio）. Also, cyclization of 2,5-bis-（arylmethylidene）cyclopentanones 2 with guanidine hydrochloride （1：1 molar ratio） in methanol in the presence of sodium methoxide afforded cyclopenta-[d]pyrimidines 3. Compound 3c has been shown to be a useful building block for the synthesis of some novel pyrimido[ 1,2-a]pyrimidines 5, 7 and 12. The structures of the newly synthesized compounds were confirmed on the basis of analytical and spectral data,

关键词： Multicomponent reaction Cyclopenta[d]pyrimidine Pyrimido[1 2-a]pyrimidine Cyclopentanone

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Soft coral Cespitularia stolonifera:New cytotoxic ceramides and gastroprotective activity

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Chinese Journal of Natural Medicines 2017年第2期15卷 105-114页

作者： Abdelsamed I.Elshamy Walaa A.El-Kashak heba M.I.Abdallah Abdelrazik H.Farrag Mahmoud I.Nassar Natural Compounds Chemistry Department National Research CentreGiza 12622Egypt Pharmacology Department National Research CentreGiza 12622Egypt Pathology Department National Research Centre Giza 12622Egypt

In the present study, a new ceramide, namely 2S, 3R-4E, 8E-2-(heptadecanoylamino)-heptadeca-4, 8-diene-1, 3-diol(1), along with four known steroids, including 24-methylcholesta-5, 24(28)-diene-3β-ol(2), 24-methylcholesta-5, 24(28)-diene-3β-acetate(3), 4-methyl-24-methylcholesta- 22-ene-3-ol(4), and cholesterol, was isolated and characterized from CH2Cl2/Me OH extract of Cespitularia stolonifera. A new acetate derivative of compound 1, termed 2S, 3R-4E, 8E-2-(heptadecanoylamino)-heptadeca-4, 8-diene-1, 3-diacetate(1a), was also prepared in the present study. All the structures were established on the basis of modern spectroscopic techniques, including FT-IR, 1D, 2D-NMR, HRESI-MS, and GC-MS, in addition of chemical methods.(-)-Alloaromadendren, ledane,(1)-alloaromadendren oxide, isoaromadendrene epoxide and(-)-caryophellen oxide were identified from the n-hexane fraction using GC-MS. The extract and the two ceramides(1) and(1a) exhibited significant cytotoxic activity against lung cancer A549 cells, while the extract and the two steroids(2) and(3) exhibited significant cytotoxic activity against breast cancer MCF-7 cells. The CH_2Cl_2/MeOH extract exhibited significant antiulcer activity in both ethanol and acetic acid induced ulcer models in rats, as evidenced by histopathological, histochemical, and biochemical examinations.

关键词： Cespitularia stolonifera Ceramide Steroids Anticancer leading constituents Antiulcer activity

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Intelligent Classification Model for Biomedical Pap Smear Images on IoT Environment

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Computers, Materials & Continua 2022年第5期71卷 3969-3983页

作者： CSS Anupama T.J.Benedict Jose heba FEid Nojood O Aljehane Fahd N.Al-Wesabi Marwa Obayya Anwer Mustafa Hilal Department Electronics and Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Computer Applications Government Arts&Science CollegeKanyakumari629401India Faculty of Science AL-Azhar UniversityCairo11651Egypt Faculty of Computers and Information Technology University of Tabuk47512Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid University62529Saudi Arabia&Faculty of Computer and ITSana’a University31220Yemen Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman University11564Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharj16278Saudi Arabia

Biomedical images are used for capturing the images for diagnosis process and to examine the present condition of organs or *** image processing concepts are identical to biomedical signal processing,which includes the investigation,improvement,and exhibition of images gathered using x-ray,ultrasound,MRI,*** the same time,cervical cancer becomes a major reason for increased women’s mortality *** cervical cancer is an identified at an earlier stage using regular pap smear *** this aspect,this paper devises a new biomedical pap smear image classification using cascaded deep forest(BPSIC-CDF)model on Internet of Things(IoT)*** BPSIC-CDF technique enables the IoT devices for pap smear image *** addition,the pre-processing of pap smear images takes place using adaptive weighted mean filtering(AWMF)***,sailfish optimizer with Tsallis entropy(SFO-TE)approach has been implemented for the segmentation of pap smear ***,a deep learning based Residual Network(ResNet50)method was executed as a feature extractor and CDF as a classifier to determine the class labels of the input pap smear *** order to showcase the improved diagnostic outcome of the BPSICCDF technique,a comprehensive set of simulations take place on Herlev *** experimental results highlighted the betterment of the BPSICCDF technique over the recent state of art techniques interms of different performance measures.

关键词： Biomedical imaging pap smear images internet of things deep learning cervical cancer disease diagnosis

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STW 5 is effective against nonsteroidal anti-inflammatory drugs induced gastro-duodenal lesions in rats

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World Journal of Gastroenterology 2019年第39期25卷 5926-5935页

作者： Mohamed T Khayyal Walaa Wadie Enas A Abd El-haleim Kawkab A Ahmed Olaf Kelber Ramy M Ammar heba Abdel-Aziz Department of Pharmacology Faculty of PharmacyCairo UniversityCairo 11562Egypt Department of Pathology Faculty of Veterinary MedicineCairo UniversityCairo 12211Egypt Steigerwald Arzneimittelwerk GmbH Bayer Consumer HealthDarmstadt 64295Germany Department of Pharmacology Faculty of PharmacyKafrelsheikh UniversityKafrelsheikh 33511Egypt

BACKGROUND Proton pump inhibitors are often used to prevent gastro-intestinal lesions induced by nonsteroidal anti-inflammatory ***,they are not always effective against both gastric and duodenal lesions and their use is not devoid of side *** To explore the mechanisms mediating the clinical efficacy of STW 5 in gastroduodenal lesions induced by nonsteroidal anti-inflammatory drugs(NSAIDs),exemplified here by diclofenac,in a comparison to *** Gastro-duodenal lesions were induced in rats by oral administration of diclofenac(5 mg/kg)for 6 successive *** group was given concurrently STW 5(5 mL/kg)while another was given omeprazole(20 mg/kg).A day later,animals were sacrificed,stomach and duodenum excised and divided into 2 segments:One for histological examination and one for measuring inflammatory mediators(tumor necrosis factorα,interleukins-1βand 10),oxidative stress enzyme(heme oxygenase-1)and apoptosis regulator(B-cell lymphoma 2).RESULTS Diclofenac caused overt histological damage in both tissues,associated with parallel changes in all parameters *** 5 and omeprazole effectively prevented these changes,but STW 5 superseded omeprazole in protecting against histological damage,particularly in the *** The findings support the therapeutic usefulness of STW 5 and its superiority over omeprazole as adjuvant therapy to NSAIDs to protect against their possible gastro-duodenal side effects.

关键词： Diclofenac STW 5 Omeprazole Gastro-intestinal lesions Inflammation

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Artificial Algae Optimization with Deep Belief Network Enabled Ransomware Detection in IoT Environment

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Computer Systems Science & Engineering 2023年第8期46卷 1293-1310页

作者： Mesfer Al Duhayyim heba G.Mohamed Fadwa Alrowais Fahd N.Al-Wesabi Anwer Mustafa Hilal Abdelwahed Motwakel Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityRiyadhSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science and Art at MuhaeylKing Khalid UniversityAbhaSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The Internet of Things(IoT)has gained more popularity in research because of its large-scale challenges and *** security was the main concern when witnessing the fast development in its applications and *** was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer ***,machine learning(ML)techniques optimally use a colossal volume of data generated by IoT *** Learning(DL)related systems were modelled for attack detection in *** the current security systems address restricted attacks and can be utilized outdated datasets for *** study develops an Artificial Algae Optimization Algorithm with Optimal Deep Belief Network(AAA-ODBN)Enabled Ransomware Detection in an IoT *** presented AAAODBN technique mainly intends to recognize and categorize ransomware in the IoT *** presented AAA-ODBN technique follows a three-stage process:feature selection,classification,and parameter *** the first stage,the AAA-ODBN technique uses AAA based feature selection(AAA-FS)technique to elect feature ***,the AAA-ODBN technique employs the DBN model for ransomware *** last,the dragonfly algorithm(DFA)is utilized for the hyperparameter tuning of the DBN technique.A sequence of simulations is implemented to demonstrate the improved performance of the AAA-ODBN *** experimental values indicate the significant outcome of the AAA-ODBN model over other models.

关键词： Internet of things deep learning cybersecurity ransomware detection feature selection

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Pivotal role of long non-coding ribonucleic acid-X-inactive specific transcript in regulating immune checkpoint programmed death ligand 1 through a shared pathway between miR-194-5p and miR-155-5p in hepatocellular carcinoma

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World Journal of Hepatology 2020年第12期12卷 1211-1227页

作者： Sara M Atwa heba handoussa Karim M Hosny Margarete Odenthal Hend M El Tayebi Pharmaceutical Biology Department German University in CairoCairo 11865Egypt Department of General Surgery Faculty of MedicineCairo UniversityCairo 11562Egypt Institute for Pathology University Hospital CologneCologne 50924Germany Molecular Pharmacology Research Group Department of Pharmacology and ToxicologyFaculty of Pharmacy and BiotechnologyGerman University in CairoCairo 11835Egypt

BACKGROUND Anti-programmed death therapy has thrust immunotherapy into the ***,such therapy has a modest response in hepatocellular carcinoma(HCC).Epigenetic immunomodulation is a suggestive combinatorial therapy with immune checkpoint ***-coding ribonucleic acid(ncRNA)driven regulation is a major mechanism of epigenetic *** the wide range of ncRNAs that co-opt in programmed cell-death protein 1(PD-1)/programmed death ligand 1(PD-L1)regulation,and based on the literature,we hypothesized that miR-155-5p,miR-194-5p and long non-coding RNAs(lncRNAs)X-inactive specific transcript(XIST)and MALAT-1 are involved in a regulatory upstream pathway for PD-1/***,nutraceutical therapeutics in cancers have received increasing ***,it is interesting to study the impact of oleuropein on the respective study key *** To explore potential upstream regulatory ncRNAs for the immune checkpoint PD-1/*** Bioinformatics tools including *** and lnCedB software were adopted to detect targeting of miR-155-5p,miR-194-5p and lncRNAs XIST and MALAT-1 to PD-L1 mRNA,*** addition,Diana tool was used to predict targeting of both aforementioned miRNAs to lncRNAs XIST and *** and normal tissue samples were collected for scanning of PD-L1,XIST and MALAT-1 *** study the interaction among miR-155-5p,miR-194-5p,lncRNAs XIST and MALAT-1,as well as PD-L1 mRNA,a series of transfections of the Huh-7 cell line was carried *** Bioinformatics software predicted that miR-155-5p and miR-194-5p can target PDL1,MALAT-1 and ***-1 and XIST were predicted to target PD-L1 ***-L1 and XIST were significantly upregulated in 23 HCC biopsies compared to healthy controls;however,MALAT-1 was barely ***-194 induced expression elevated the expression of PD-L1,XIST and ***,overexpression of miR-155-5p induced the upregulation of PD-L1 and XIST,while it had a negative impact on MA

关键词： Hepatocellular carcinoma X-inactive specific transcript MiR-155-5p MiR-194-5p Programmed cell-death protein 1/Programmed death ligand 1 Immune checkpoint

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Coati Optimization-Based Energy Efficient Routing Protocol for Unmanned Aerial Vehicle Communication

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Computers, Materials & Continua 2023年第6期75卷 4805-4820页

作者： hanan Abdullah Mengash hamed Alqahtani Mohammed Maray Mohamed K.Nour Radwa Marzouk Mohammed Abdullah Al-hagery heba Mohsen Mesfer Al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial Intelligence and Unit of CybersecurityKing Khalid UniversityAbha62529Saudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Sciences College of Computing and Information SystemsUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah52571Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile *** difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing *** the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same ***,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance analysis for selecting the optimum routing *** this motivation,this study modelled a new Coati Optimization Algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)*** presented COAER-UAVC technique establishes effective routes for communication between the *** is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from ***,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC *** experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.

关键词： Artificial intelligence unmanned aerial vehicle data communication routing protocol energy efficiency

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Battle Royale Optimization with Fuzzy Deep Learning for Arabic Sentiment Classification

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Computer Systems Science & Engineering 2023年第8期46卷 2619-2635页

作者： Manar Ahmed hamza hala J.Alshahrani Jaber S.Alzahrani heba Mohsen Mohamed I.Eldesouki Mohammed Rizwanullah Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkah 24211Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Aspect-Based Sentiment Analysis(ABSA)on Arabic corpus has become an active research topic in recent *** refers to a fine-grained Sentiment Analysis(SA)task that focuses on the extraction of the conferred aspects and the identification of respective sentiment polarity from the provided *** of the prevailing Arabic ABSA techniques heavily depend upon dreary feature-engineering and pre-processing tasks and utilize external sources such as *** literature,concerning the Arabic language text analysis,the authors made use of regular Machine Learning(ML)techniques that rely on a group of rare sources and *** sources were used for processing and analyzing the Arabic language content like ***,an important challenge in this domain is the unavailability of sufficient and reliable *** this background,the current study introduces a new Battle Royale Optimization with Fuzzy Deep Learning for Arabic Aspect Based Sentiment Classification(BROFDL-AASC)*** aim of the presented BROFDL-AASC model is to detect and classify the sentiments in the Arabic *** the presented BROFDL-AASC model,data pre-processing is performed at first to convert the input data into a useful ***,the BROFDL-AASC model includes Discriminative Fuzzy-based Restricted Boltzmann Machine(DFRBM)model for the identification and categorization of ***,the BRO algorithm is exploited for optimal fine-tuning of the hyperparameters related to the FBRBM *** scenario establishes the novelty of current *** performance of the proposed BROFDL-AASC model was validated and the outcomes demonstrate the supremacy of BROFDL-AASC model over other existing models.

关键词： Arabic corpus aspect based sentiment analysis arabic language deep learning battle royale optimization natural language processing

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