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Optimal Deep Belief Network Enabled Cybersecurity Phishing Email Classification

Computer Systems Science & Engineering 2023年第3期44卷 2701-2713页

作者： Ashit Kumar Dutta T.meyyappan Basit Qureshi majed alsanea Anas Waleed Abulfaraj manal m.al faraj Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Science Alagappa UniversityKaraikudi630003India Department of Computer Science Prince Sultan UniversityRiyadh11586Kingdom of Saudi Arabia Department of Computing Arabeast CollegesRiyadh11583Kingdom of Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah23613Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

Recently,developments of Internet and cloud technologies have resulted in a considerable rise in utilization of online media for day to day *** results in illegal access to users’private data and compromises *** is a popular attack which tricked the user into accessing malicious data and gaining the *** identification of phishing emails can be treated as an essential process in the domain of *** article focuses on the design of bio-geography based optimization with deep learning for Phishing Email detection and classification(BBODL-PEDC)*** major intention of the BBODL-PEDC model is to distinguish emails between legitimate and *** BBODL-PEDC model initially performs data pre-processing in three levels namely email cleaning,tokenization,and stop word ***,TF-IDF model is applied for the extraction of useful feature ***,optimal deep belief network(DBN)model is used for the email classification and its efficacy can be boosted by the BBO based hyperparameter tuning *** performance validation of the BBODL-PEDC model can be performed using benchmark dataset and the results are assessed under several *** comparative studies reported the superior outcomes of the BBODL-PEDC model over the recent approaches.

关键词： Cybersecurity phishing email data classification deep learning biogeography based optimization hyperparameter tuning

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Complex Decision modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

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Computer modeling in Engineering & Sciences 2024年第5期139卷 1893-1932页

作者： Nadeem Salamat muhammad Kamran Shahzaib Ashraf manal Elzain mohammed Abdulla Rashad Ismail mohammed m.al-Shamiri Institute of mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Department of mathematics Thal University BhakkarPunjab30000Pakistan Department of mathematics Faculty of Science and ArtsKing Khalid UniversityMuhayl Assir61913Saudi Arabia

The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and *** paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse *** it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,*** use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying *** present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these *** operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and *** highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making *** use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted ***,we developed a novel technique by combining the IFSs with quaternion *** establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making *** the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately wo

关键词： Intuitionistic fuzzy set quaternion numbers fuzzy logic decision-making rough set

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Tensile Strain Capacity Prediction of Engineered Cementitious Composites (ECC) Using Soft Computing Techniques

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Computer modeling in Engineering & Sciences 2024年第3期138卷 2925-2954页

作者： Rabar H.faraj Hemn Unis Ahmed Hardi Saadullah Fathullah alan Saeed Abdulrahman Farid Abed Civil Engineering Department University of HalabjaHalabjaIraq University of Sulaimani College of EngineeringCivil Engineering DepartmentSulaimaniIraq Civil Engineering Department Komar University of Science and TechnologySulaimaniIraq Department of Engineering Kurdistan Institution for Strategic Studies and Scientific ResearchesSulaimaniIraq Department of Civil Engineering American University of SharjahSharjah26666UAE

Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is *** order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional *** concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched *** a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes ***,the effort required for laboratory trial batches to determine the TSC is *** achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(mLR),and m5P-tree model(m5P),are investigated and employed to predict the TSCof ECCmixtures containing fly *** from115 mixtures are gathered and analyzed to develop a new *** input variables include mixture proportions,fiber length and diameter,and the time required for curing the various *** model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(mAE),scatter index(SI),root mean squared error(RmSE),and objective function(OBJ)***,the ANN model outperforms the others in predicting the TSC of the ECC,with RmSE,mAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.

关键词： Engineered cementitious composites fly ash curing time tensile strain capacity modeling

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Intelligent Smart Grid Stability Predictive model for Cyber-Physical Energy Systems

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Computer Systems Science & Engineering 2023年第2期44卷 1219-1231页

作者： Ashit Kumar Dutta manal al faraj Yasser albagory mohammad zeid m.alzamil Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

A cyber physical energy system(CPES)involves a combination of pro-cessing,network,and physical *** smart grid plays a vital role in the CPES model where information technology(IT)can be related to the physical *** the same time,the machine learning(mL)modelsﬁnd useful for the smart grids integrated into the CPES for effective decision ***,the smart grids using mL and deep learning(DL)models are anticipated to lessen the requirement of placing many power plants for electricity *** this aspect,this study designs optimal multi-head attention based bidirectional long short term memory(OmHA-mBLSTm)technique for smart grid stability predic-tion in *** proposed OmHA-mBLSTm technique involves three subpro-cesses such as pre-processing,prediction,and hyperparameter *** OmHA-mBLSTm technique employs min-max normalization as a pre-proces-sing ***,the mBLSTm model is applied for the prediction of stability level of the smart grids in *** the same time,the moth swarm.algorithm(mHA)is utilized for optimally modifying the hyperparameters involved in the mBLSTm *** ensure the enhanced outcomes of the OmHA-mBLSTm technique,a series of simulations were carried out and the results are inspected under several *** experimental results pointed out the better outcomes of the OmHA-mBLSTm technique over the recent models.

关键词： Stability prediction smart grid cyber physical energy systems deep learning data analytics moth swarm.algorithm

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Optimal Sparse Autoencoder Based Sleep Stage Classification Using Biomedical Signals

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Computer Systems Science & Engineering 2023年第2期44卷 1517-1529页

作者： Ashit Kumar Dutta Yasser albagory manal al faraj Yasir A.m.Eltahir Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of Respiratory Care College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

The recently developed machine learning(mL)models have the ability to obtain high detection rate using biomedical ***,this article develops an Optimal Sparse Autoencoder based Sleep Stage Classiﬁcation model on Electroencephalography(EEG)Biomedical Signals,named OSAE-SSCEEG *** major intention of the OSAE-SSCEEG technique is toﬁnd the sleep stage disorders using the EEG biomedical *** OSAE-SSCEEG technique primarily undergoes preprocessing using min-max data normalization ***,the classiﬁcation of sleep stages takes place using the Sparse Autoencoder with Smoothed Regularization(SAE-SR)with softmax(Sm)***,the parameter optimization of the SAE-SR technique is carried out by the use of Coyote Optimization algorithm(COA)and it leads to boosted classiﬁcation efﬁ*** order to ensure the enhanced performance of the OSAE-SSCEEG technique,a wide ranging simulation analysis is performed and the obtained results demonstrate the betterment of the OSAE-SSCEEG tech-nique over the recent methods.

关键词： Biomedical signals EEG sleep stage classiﬁcation machine learning autoencoder softmax parameter tuning

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Cat Swarm with Fuzzy Cognitive maps for Automated Soil Classification

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Computer Systems Science & Engineering 2023年第2期44卷 1419-1432页

作者： Ashit Kumar Dutta Yasser albagory manal al faraj majed alsanea Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of Computing Arabeast CollegesRiyadh11583Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

Accurate soil prediction is a vital parameter involved to decide appro-priate crop,which is commonly carried out by the *** an auto-mated soil prediction tool helps to considerably improve the efﬁcacy of the *** the same time,fuzzy logic(FL)approaches can be used for the design of predictive models,particularly,Fuzzy Cognitive maps(FCms)have involved the concept of uncertainty representation and cognitive *** other words,the FCm is an integration of the recurrent neural network(RNN)and FL involved in the knowledge engineering *** this aspect,this paper introduces effective fuzzy cognitive maps with cat swarm optimization for automated soil classiﬁca-tion(FCmCSO-ASC)*** goal of the FCmCSO-ASC technique is to identify and categorize seven different types of *** accomplish this,the FCmCSO-ASC technique incorporates local diagonal extrema pattern(LDEP)as a feature extractor for producing a collection of feature *** addition,the FCmCSO model is applied for soil classiﬁcation and the weight values of the FCm model are optimally adjusted by the use of CSO *** exam-ining the enhanced soil classiﬁcation outcomes of the FCmCSO-ASC technique,a series of simulations were carried out on benchmark dataset and the experimen-tal outcomes reported the enhanced performance of the FCmCSO-ASC technique over the recent techniques with maximum accuracy of 96.84%.

关键词： Soil classiﬁcation intelligent models fuzzy cognitive maps cat swarm optimization fuzzy logic

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Optimal Weighted Extreme Learning machine for Cybersecurity Fake News Classification

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Computer Systems Science & Engineering 2023年第3期44卷 2395-2409页

作者： Ashit Kumar Dutta Basit Qureshi Yasser albagory majed alsanea manal al faraj Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Science Prince Sultan UniversityRiyadh11586Kingdom of Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of Computing Arabeast CollegesRiyadh11583Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

Fake news and its significance carried the significance of affecting diverse aspects of diverse entities,ranging from a city lifestyle to a country global relativity,various methods are available to collect and determine fake *** recently developed machine learning(mL)models can be employed for the detection and classification of fake *** study designs a novel Chaotic Ant Swarm with Weighted Extreme Learning machine(CAS-WELm)for Cybersecurity Fake News Detection and *** goal of the CAS-WELm technique is to discriminate news into fake and *** CAS-WELm technique initially pre-processes the input data and Glove technique is used for word embed-ding ***,N-gram based feature extraction technique is derived to gen-erate feature ***,WELm model is applied for the detection and classification of fake news,in which the weight value of the WELm model can be optimally adjusted by the use of CAS *** performance validation of the CAS-WELm technique is carried out using the benchmark dataset and the results are inspected under several *** experimental results reported the enhanced outcomes of the CAS-WELm technique over the recent approaches.

关键词： Cybersecurity cybercrime fake news data classification machine learning metaheuristics

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Return to Dialysis after Kidney Graft Failure

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Open Journal of Nephrology 2024年第2期14卷 240-252页

作者： Ikram Ftaimi Soukaina Sakab manal Chattahi Tarik Bouattar Loubna Benamar Rabia Bayahia Naima Ouzeddoun Service de Nphrologie-Dialyse-Transplantationrnale CHU Ibn Sina Rabat Universit Mohammed V Rabat Morocco

Introduction: The transition period from renal transplantation to dialysis is associated with high morbidity and mortality. The aim of this study is to describe the clinical and paraclinical characteristics, therapeutic management and evolutionary profile of patients returning to dialysis after kidney graft failure. material and methods: This was a retrospective, descriptive study conducted in the Nephrology-Dialysis-Renal Transplant Department at university hospital IbnSina between January 1998 and December 2021. We included all renal transplant recipients who had experienced kidney graft dysfunction and returned to dialysis. Patients with a follow-up after return to dialysis of less than 1 year were excluded. Results: Among 166 renal transplant recipients, 20 returned to dialysis after a median renal graft life of 85.5 months [42 - 186], corresponding to a prevalence of 12%. The mean age of our patients was 38.7 ± 11.9 years, with a m/F sex ratio of 2.3. Dialysis was initiated urgently in 10 patients (50%). Hemodialysis was the most commonly used modality (75%). Central venous catheterization was used in 35% of cases, including tunneled catheters. General condition is impaired in all patients, with persistent hypertension in 70% of cases. mean uremia was 2.35 ± 0.8 g/l, mean creatinine 116 ± 48.3 mg/l, giving a mean GFR of 5.1 ± 2.2 ml/min. mean albuminemia was 32.9 ± 6 g/l and mean hemoglobinemia 8.6 ± 1.9 g/dl. During the first year of follow-up, none of the patients died. However, 13 patients required hospitalization, with a mean length of stay of 15 days. Eight patients were hospitalized for infections and 5 for renal graft intolerance syndrome. After a mean follow-up of 22 months, 6 patients were detransplanted following graft necrosis. Conclusion: Return to dialysis after RT is fraught with a high rate of complications. The management of these patients must be optimized to improve their vital prognosis and quality of life.

关键词： Kidney Graft Failure Dialysis Detransplantation Immunosuppression

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Characterization and antimicrobial,antioxidant,and anti-proliferative activities of green synthesized magnesium oxide nanoparticles with shoot extracts of Plicosepalus curviflorus

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Asian Pacific Journal of Tropical Biomedicine 2023年第7期13卷 315-324页

作者： Reem Hamoud alrashoudi manal Abudawood Ayesha mateen Hajera Tabassum Noura Ibrahem.alghumlas Sabiha Fatima Basmah almaarik Farah maqsood Nawal m.al musayeib musarat Amina Clinical Laboratory Sciences Department College of Applied Medical SciencesKing Saud UniversityRiyadh 12372Saudi Arabia Department of Optometry and Vision Science College of Applied Medical ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of Pharmacognosy College of PharmacyKing Saud UniversityRiyadh 11495P.O.Box 22452Saudi Arabia

Objective:To synthesize magnesium oxide nanoparticles using ethanol extract of shoots of Plicosepalus curviflorus(PC-mgONPs)and evaluate the antimicrobial,antioxidant,and anti-proliferative activities of ***:The green synthesized PC-mgONPs were characterized by ultraviolet-visible(UV),Fourier-transform infrared spectroscopy,zeta potential,energy dispersive X-ray,and scanning electron ***,we investigated total antioxidant capacity and antimicrobial and anti-proliferative activities using breast cancer cell lines(mDA-231).Results:The UV spectrum of PC-mgONPs showed a sharp absorption peak at 300 *** presence of magnesium,oxygen,and sodium was confirmed by energy dispersive X-ray *** electron microscopy revealed PC-mgONPs as roughly spherical granular structures with sizes ranging from 20.0 to ***-mgONPs showed considerable antimicrobial activities against Escherichia coli,Staphylococcus aureus,methicillin-resistant Staphylococcus aureus,Pseudomonas aeruginosa and Candida albicans with zones of inhibition of 11-17 *** addition,total antioxidant capacity and anti-proliferative activity of PC-mgONPs against mDA-231 cells were ***:The synthesized PC-mgONPs could be a potent antimicrobial,antioxidant and anti-cancer agent,which needs further investigation.

关键词： PC-mgONPs Plicosepalus curviflorus FTIR Antimicrobial Cell viability Antioxidant

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Hepatitis B genotypes: Relation to clinical outcome in patients with chronic hepatitis B in Saudi Arabia

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World Journal of Gastroenterology 2006年第43期12卷 7019-7024页

作者： Ayman A Abdo Badr m.al-Jarallah Faisal m Sanai Ahmad S Hersi Khalid al-Swat Nahla A Azzam manal al-Dukhayil Amira al-maarik Faleh Z al-Faleh Gastroenterology Division Faculty of Medicine King Saud University Riyadh Saudi Arabia Gastroenterology Unit Department of Medicine McGill University Montreal Canada Hepatology Division Department of Medicine Riyadh Military Hospital Riyadh Saudi Arabia

AIm： To identify the most common hepatitis B virus （HBV） genob/pe in Saudi Arabia, and correlate the prevailing genob/pes with the clinical outcome of patients. mETHODS： Patients were consecutively recruited from the hepatology clinics of two tertiary care referral centers. Patients were categorized into 4 different groups： group 1, patients with hepatitis B and normal liver enzymes; group 2, patients with hepatitis B and abnormal liver enzymes but without cirrhosis; group 3, patients with hepatitis B and liver cirrhosis; group 4, patients with hepatitis B and hepatocellular carcinoma. all patients had a positive hepatitis B surface antigen （HBsAg）. Genob/ping of HBV was performed by nested PCR-mediated amplification of the target sequence and hybridization with sequence-specific oligonucleotides. RESULTS： Seventy patients were enrolled in this study. They were predominantly male （72.9%） in their midforty＇s （mean age 47 years）. Forty-nine （70%） patients were hepatitis B envelope antigen （HBeAg） negative. The majority of patients （64%） acquired HBV through unknown risk factors. Hepatitis B genob/ping revealed that 57 patients （81.4%） were genob/pe D, 1 patient （1.4%） had genob/pe A, 1 patient （1.4%） had genotype C, and 4 patients （5.7%） had genob/pe E, while 7 patients （10%） had mixed genob/pe （4 patients ADG, 1 patient DE, 1 patient DF, and 1 patient ADFG）. Based on univariate analysis of genob/pe D patients, significant predictors of advanced liver disease were age, gender, aspartate transaminase, alanine transaminase, albumin,bilirubin, and alkaline phosphatase （all P 〈 0.001）. In multivariate analysis decreased hemoglobin （r = -0.05; 95% CI： -0.08 to -0.03; P = 0.001） and albumin levels （r = -0.004; 95% CI： -0.007 to -0.001; P = 0.002） were highly significant predictors of advanced liver disease. In patients with HBV genotype D, HBeAg negativity was found to increase across advancing stages of liver disease （P = 0.024）. CONCLUSION： This study highlights tha

关键词： Hepatitis B virus Genotype D Cirrhosis Hepatocellular carcinoma Saudi Arabia

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