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A Hybrid Classification and Identification of Pneumonia Using African Buffalo Optimization and CNN from Chest X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2497-2517页

作者： Nasser Alalwan Ahmed I.Taloba Amr Abozeid Ahmed ibrahim Alzahrani Ali H.Al-Bayatti Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Information System Department Faculty of Computers and InformationAssiut UniversityAssiutEgypt Mathematics Department Faculty of ScienceAl-Azhar UniversityCairoEgypt Cyber Technology Institute(CTI) De Montfort UniversityLeicesterUK

An illness known as pneumonia causes inflammation in the *** there is so much information available fromvarious X-ray images,diagnosing pneumonia has typically proven *** improve image quality and speed up the diagnosis of pneumonia,numerous approaches have been *** date,several methods have been employed to identify *** Convolutional Neural Network(CNN)has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and ***,these methods are complex,inefficient,and imprecise to analyze a big number of *** this paper,a new hybrid method for the automatic classification and identification of Pneumonia from chest X-ray images is *** proposed method(ABOCNN)utilized theAfrican BuffaloOptimization(ABO)algorithmto enhanceCNNperformance and *** Weinmed filter is employed for pre-processing to eliminate unwanted noises from chest X-ray images,followed by feature extraction using the Grey Level Co-Occurrence Matrix(GLCM)*** features are then selected from the dataset using the ABO algorithm,and ultimately,high-performance deep learning using the CNN approach is introduced for the classification and identification of *** results on various datasets showed that,when contrasted to other approaches,the ABO-CNN outperforms them all for the classification *** proposed method exhibits superior values like 96.95%,88%,86%,and 86%for accuracy,precision,recall,and F1-score,respectively.

关键词： African buffalo optimization convolutional neural network pneumonia X-ray

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Deciphering resistancemechanisms and novel strategies to overcome drug resistance in ovarian cancer:a comprehensive review

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Oncology Research 2024年第5期32卷 831-847页

作者： EFFAT ALEMZADEH LEILA ALLAHQOLI AFROOZ MAZIDIMORADI ESMAT ALEMZADEH FAHIMEH GHASEMI HAMID SALEHINIYA ibrahim ALKATOUT Infectious Diseases Research Center Birjand University of Medical SciencesBirjandIran Department of Midwifery Ministry of Health and Medical EducationTehranIran Student Research Committee Shiraz University of Medical SciencesShirazIran Department of Biotechnology Faculty of MedicineBirjand University of Medical SciencesBirjandIran Cellular and Molecular Research Center Birjand University of Medical SciencesBirjandIran Social Determinants of Health Research Center Birjand University of Medical SciencesBirjandIran Kiel School of Gynaecological Endoscopy Campus KielUniversity Hospitals Schleswig-HolsteinKielGermany

Ovarian cancer is among the most lethal gynecological cancers,primarily due to the lack of specific symptoms leading to an advanced-stage diagnosis and resistance to *** resistance(DR)poses the most significant challenge in treating patients with existing *** Food and Drug Administration(FDA)has recently approved three new therapeutic drugs,including two poly(ADP-ribose)polymerase(PARP)inhibitors(olaparib and niraparib)and one vascular endothelial growth factor(VEGF)inhibitor(bevacizumab)for maintenance ***,resistance to these new drugs has ***,understanding the mechanisms of DR and exploring new approaches to overcome them is crucial for effective *** this review,we summarize the major molecular mechanisms of DR and discuss novel strategies to combat DR.

关键词： Chemotherapy Drug resistance mechanisms Ovarian cancer PARP inhibitors VEGF inhibitor

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Comparison of vergence mechanisms between university students with good and poor sleep quality

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International Journal of Ophthalmology(English edition) 2024年第2期17卷 353-358页

作者： Pui Juan Woi Joyce Yi Ling Lu Mohd Izzuddin Hairol Wan Nur Amirah ibrahim Optometry and Vision Science Programme Center for Community Health Studies(ReaCH)Faculty of Health SciencesUniversiti Kebangsaan MalaysiaKuala Lumpur 50300Malaysia Centre of Optometry Studies Faculty of Health SciencesUniversiti Teknologi MARASelangor BranchPuncak Alam CampusSelangor 42300Malaysia

AIM:To compare the vergence mechanisms between good and poor sleepers in university ***:A total of 64 university students were recruited in this *** validated Malay version of Pittsburgh Sleep Quality Index questionnaire(PSQI-M)was used to measure the participants’sleep quality over the past *** were categorized as good sleepers(n=32)and poor sleepers(n=32)based on the PSQI-M *** and fusional vergences were measured at distance and ***-Whitney U test was used to compare heterophoria,negative fusional vergence(NFV),and positive fusional vergence(PFV)at distance and near between good and poor *** correlation analysis was used to study the relationship between PSQI-M score and PFV at ***:Both distance and near heterophorias were not significantly different between good and poor sleepers(P>0.05).There was a difference in distance PFV(P0.05).Distance PFV was negatively correlated with PSQI-M score(rs=-0.33,P<0.05).CONCLUSION:University students with poor sleep quality demonstrates a reduced ability to maintain fusion with increasing convergence demand at *** quality assessment during binocular vision examination in university students is recommended.

关键词： binocular vision vergence sleep quality university students

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A Hybrid Model for Improving Software Cost Estimation in Global Software Development

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Computers, Materials & Continua 2024年第1期78卷 1399-1422页

作者： Mehmood Ahmed Noraini B.ibrahim Wasif Nisar Adeel Ahmed Muhammad Junaid Emmanuel Soriano Flores Divya Anand Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit RajaBatu Pahat86400Malaysia Department of Computer Science COMSATS University Wah Cantt CampusIslamabad47010Pakistan Department of Information Technology The University of HaripurKhyber Pakhtunkhwa22620Pakistan Engineering Research Innovation Group Universidad Europea del AtlanticoSantander39011Spain

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert *** models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate *** addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation ***,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost *** study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these *** proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry *** article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost *** the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing *** findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

关键词： Artificial neural networks COCOMO II cost drivers global software development linear regression software cost estimation

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Quantification of Silicon (SI) and Silicon Dioxide (SiO₂) from the Nafud Desert-Al-Qassim Region, Kingdom of Saudi Arabia Using XRD Analysis

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Advances in Materials Physics and Chemistry 2024年第5期14卷 67-75页

作者： Nagwa ibrahim Mohamed Department of Physics College of Science Qassim University Buraydah Saudi Arabia

This research was conducted in the Qassim region, Kingdom of Saudi Arabia. The goal of this research is to determine the percentage of silicon in the Rub al-Khali desert. Samples were collected from four cities located in the Al-Qassim Region of Saudi Arabia (Uyun Al-Jawa, Al-Fuwailiq, Al-Sulaibiya, and Al-Qawara), from three distinct depths (the earth’s surface, 50 cm, and 100 cm). The percentages of silicon in these places vary between the highest value for silicon dioxide, which is 74.47 m/m%, and 34.8 m/m% for silicon in Al-Qawara city at a depth of 100 cm. We used an x-ray fluorescence (XRF) instrument to evaluate the samples. There are high percentage of both silica and silicon in the Nafud desert. Studies have shown that these ratios can help investors benefit from an element of Silicon and silicon dioxide, so the sands of the Nafud desert is sufficient for extracting Silicon and silica in huge quantities. This may transform the Kingdom into a leading country in the global computer technology industry that depends on silicon extracted from the desert sands, the most important of which are microcomputer data processing devices.

关键词： Silica Sand Dispersive X-Ray Fluorescence (EDXRF) Analyzer Solar Cells Nafud Desert Al-Qawwarh

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan ibrahim M.Mehedi Shaikh Abdul Latif Md.Masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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Study the Effect of Thickness on the Performance of PM6:Y6 Organic Solar Using SCAPS Simulation

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Advances in Materials Physics and Chemistry 2024年第4期14卷 55-65页

作者： Nagwa ibrahim Mohammed ibrahim Amnah Mohammed Elharbi Abdulrahman Albadri Department of Physics Science College Qassim University Buraydah Saudi Arabia Department of Physics Science College Al Baha University Baha Saudi Arabia Microelectronics and Semiconductors Institute King Abdulaziz City for Science and Technology Riyadh Saudi Arabia

In this study, organic solar cells (OSCs) with an active layer, a blend of polymer of non-fullerene (NFA) Y6 as an acceptor, and donor PBDB-T-2F as donor were simulated through the one-dimensional solar capacitance simulator (SCAPS-1D) software to examine the performance of this type of organic polymer thin-film solar cell by varying the thickness of the active layer. PFN-Br interfacial layer entrenched in OPV devices gives overall enhanced open-circuit voltage, short-circuit current density and fill factor thus improving device performance. PEDOT: PSS is an electro-conductive polymer solution that has been extensively utilized in solar cell devices as a hole transport layer (HTL) due to its strong hole affinity, good thermal and mechanical stability, high work function, and high transparency in the visible range. The structure of the organic solar cell is ITO/PEDOT: PSS/BTP-4F: PBDB-T-2F/PFN-Br/Ag. Firstly, the active layer thickness was optimized to 100 nm;after that, the active-layer thickness was varied up to 900 nm. The results of these simulations demonstrated that the active layer thickness improves efficiency significantly up to 500 nm, then it decreased with increasing the thickness of the active layer from 600 nm, also notice that the short circuit current and the fill factor decrease with increasing the active layer from 600 nm, while the open voltage circuit increased with increasing the thickness of the active layer. The optimum thickness is 500 nm.

关键词： Organic Solar Cells PEDOT:PSS BTP-4F (Y6) PBDB-T-2F (PM6) PFN-Br SCAPS 1D

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On the Zeros of a Special Class of Polynomials

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Journal of Mathematical Research with Applications 2024年第4期44卷 470-474页

作者： Mahnaz Shafi CHISHTI Vipin Kumar TYAGI Mohammad ibrahim MIR School of Basic and Applied Sciences Shobhit Institute of Engineering and Technology (Deemed to be University) Department of Mathematics University of KashmirSouth Campus

Let P be a complex polynomial of the form P （z）=（λz-a）mΠj=1n-m（z-zj）,where|zj|≥1,1≤j≤*** aim of this paper is to obtain generalisation of a result due to Zargar and Manzoor and a result due to Mir,Nazir and *** shall also obtain an interesting bound which contains the zeros of the second derivative of P （z）.

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Effects of friction stir processing and nano-hydroxyapatite on the microstructure,hardness,degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications

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Journal of Magnesium and Alloys 2024年第1期12卷 209-224页

作者： Bo Wu Farazila Yusof Fuguo Li Huan Miao A.R.Bushroa Mohd Ridha Bin Muhamad Irfan Anjum Badruddin Mahmoud Z.ibrahim Department of Mechanical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur 50603Malaysia Centre of Advanced Manufacturing and Material Processing(AMMP Centre) Universiti MalayaKuala Lumpur 50603Malaysia Center of Foundation studies in Science Universiti MalayaKuala Lumpur 50603Malaysia State Key Laboratory of Solidification Processing School of Materials Science and EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Mechanical Engineering Department College of EngineeringKing Khalid UniversityAbha 61421Saudi Arabia Design and Production Engineering Faculty of EngineeringAin Shams UniversityCairo 11517Egypt

Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural ***,the rapid degradation of magnesium alloys in biological media hinders successful *** of microstructure,as well as reinforcement particles can significantly improve the degradation *** this work,multi-pass friction stir processing(FSP)was proposed to synthesize WE43/nano-hydroxyapatite(n HA)surface composite,the microstructure,reinforced particle distribution,micro-hardness,corrosion behavior and in-vitro bioactivity were *** subsequent FSP passes of WE43 alloy and WE43/n HA composite refined the grain size which was reduced by 94.29%and 95.92%(2.63 and 1.88μm,respectively)compared to base metal after three *** resulted in increasing the microhardness by 120%(90.86 HV0.1)and 135%(105.59 HV0.1)for the WE43 and WE43-n HA,*** is found that increasing FSP passes improved the uniform distribution of n HA particles within the composite matrix which led to improved corrosion resistance and less degradation *** corrosion rate of the FSPed WE43/n HA composite after three passes was reduced by 38.2%(4.13 mm/year)and the degradation rate was reduced by 69.7%(2.87 mm/y).This is attributed to secondary phase(Mg24Y5and Mg41Nd5)particle fragmentation and redistribution,as well as a homogeneous distribution of n ***,the growing Ca-P and Mg(OH)2layer formed on the surface represented a protective layer that reduced the degradation *** wettability test revealed a relatively hydrophilic surface with water contact angle of 49.1±2.2°compared to 71.2±2.1°for base ***,biomineralization test showed that apatite layer grew after immersion 7d in simulated body fluid with atomic ratio of Ca/P 1.60 approaching the stoichiometric ratio(1.67)indicating superior bioactivity of FSPed WE43/n HA composite after three *** results raise that the grain refinement by FSP and introduction of n HA partic

关键词： Friction stir processing Magnesium-based composite Nano-hydroxyapatite Corrosion behavior In-vitro bioactivity

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Hydrate Prevention Strategies and the Associated Cost in the Gulf of Mexico

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World Journal of Engineering and Technology 2024年第2期12卷 286-309页

作者： ibrahim Ninalowo Bahman Tohidi Institute of Petroleum Engineering Heriot Watt University Edinburgh UK

With the petroleum industry endeavoring to develop promising oil and gas in deeper water, gas hydrates prevention is a serious concern for oil and gas producing companies producing at conditions in the hydrate region. This paper details lessons learned from the successful field deployment of AA LDHI and proper implementation strategies used for 3 different practical fields as case studies in the Gulf of Mexico. From the 3 field experiences, the AA LDHI has been used to replace the conventional thermodynamic hydrate inhibitor due to its numerous benefits during steady state operations and transition operations where AA LDHI is injected prior to extended shut in and restart for fields producing at low water cut. However, the strategy to develop a cost effective chemical management of hydrates for fields producing at high water cut is by pumping methanol or diesel to push down the wellbore fluid below the mud line during planned and unplanned shut-ins to delay water production, it also secures the riser with non hydrate fluids. This illustrates how the AA LDHIs are used in conjunction with more conventional hydrate management approaches to reach an optimal cost effective field hydrate management solution. However, this shows that the key to overall success of hydrate prevention is a full integration of a good front end design, a comprehensive deployment and an effective down hole monitoring system.

关键词： Flow Assurance Hydrate Production Chemistry Hydrate Inhibitor Hydrate Prevention Strategies Deep Water Oil and Gas Production Hydrate Blockage

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