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Real-Time Multi-Class Infection Classification for Respiratory Diseases

Computers, Materials & Continua 2022年第11期73卷 4157-4177页

作者： ahmed el.Shafee Walid el-Shafai abdulaziz Alarifi mohammed Amoon Aman Singh Moustafa H.Aly Department of electrical Engineering Faculty of EngineeringAhram Canadian UniversityGizaEgypt Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Science Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Higher Polytechnic School Universidad Europea del AtlánticoSantander39011Spain electronics and Communications Engineering Department College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt

Real-time disease prediction has emerged as the main focus of study in the field of computerized *** disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable,consistent,and timely,successfully lowering mortality rates,particularly during endemics and *** prevent this pandemic’s rapid and widespread,it is vital to quickly identify,confine,and treat affected *** need for auxiliary computer-aided diagnostic(CAD)systems has *** recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 *** advanced convolutional neural network(CNN)architectures in conjunction with radiological imaging makes it possible to provide rapid,accurate,and extremely useful susceptible *** research work proposes a methodology for real-time detection of COVID-19 infections caused by the Corona *** purpose of this study is to offer a two-way COVID-19(2WCD)diagnosis prediction deep learning system that is built on Transfer Learning Methodologies(TLM)and features customized fine-tuning on top of fully connected layered pre-trained CNN architectures.2WCD has applied modifications to pre-trained models for better *** is designed and implemented to improve the generalization ability of the classifier for binary and multi-class *** with the ability to differentiate COVID-19 and No-Patient in the binary class model and COVID-19,No-Patient,and Pneumonia in the multi-class model,our framework is augmented with a critical add-on for visually demonstrating infection in any tested radiological image by highlighting the affected region in the patient’s lung in a recognizable color *** proposed system is shown to be extremely robust and reliable for real-time COVID-19 diagnostic *** can also be used to forecast other lung-related *** the system can assist medical practitioner

关键词： COVID-19 real-time computerized disease prediction intelligent disease identification framework CAD systems X-rays CT-scans CNN real-time detection of COVID-19 infections

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Impact of Seawater Irrigation on seed germination and seedling growth of Ten Bread Wheat(Triticum aestivum L.)Genotypes

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Life Research 2024年第2期7卷 32-37页

作者： Sami mohammed Salih ahmed Amrajaa abdulrraziq Department of Biology Faculty of EducationOmar Al-Mukhtar UniversityAl-BaydaLibya

Objective:Seawater leakage in Al-Jabal Al-Akhdar East Libya's coastal areas is one of the most biggest obstacles to farmers obtaining a highly productive *** a result,the experiment was conducted in a laboratory to find out the impact of irrigation with seawater on the salt tolerance of Acsad Bread wheat ***:Ten genotypes(1398,1492,1514,1522,1524,1536,1538,1544,1550,and 1562),obtained from the Arab Center for the Studies of Arid Zones and Dry Lands Acsad,were used in the study,10 seeds of each genotype with three repetitions were germinated under four seawater concentrations(10,20,30 and 40%).Results:The results showed that there were highly significant(P≤0.05)differences in the genotypes’response to all salinity concentrations,Which led to decreasing germination percentage,delaying the average germination time,and decreasing radical/plumule length and seedling fresh/dry weight compared with a *** noted genotypes(1524,1522 and 1514)were able to germinate in all concentrations of seawater,and gave the best average for all the studied ***,the study indicated that a concentration of seawater of 40%was the most toxic for all wheat *** results of this study categorize the wheat genotypes into tolerant genotypes(1524,1522 and 1514),moderate tolerant(1492,1536),and sensitive(1398,1538,1544,1550 and 1562).Conclusion:The results concluded that the possibility of wheat crops agriculture into tolerant in Libyan coastal locations in which seawater concentration did not exceed 30%.

关键词： acsad bread wheat Libyan coastal locations salinity tolerance seawater irrigation

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Expression levels of pro-inflammatory interleukin-8 and certain antimicrobial peptides in concurrent with bacterial conjunctivitis

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International Journal of Ophthalmology(English edition) 2021年第5期14卷 666-675页

作者： Alaa el-Dien Shawky Hosny Zeinab el-Demerdash el-Bazza mohammed abdelhalim Ramadan Maha ahmed Shafik Mahmoud ahmed Shafeek Rania abdelmonem Khattab Microbiology and Immunology Department Faculty of PharmacyCairo UniversityKasr Al-Aini 11562CairoEgypt Drug Radiation Research Department National Center for Radiation Research and TechnologyAtomic Energy AuthorityCairo 9621Egypt Ophthalmology Department Faculty of medicineAL-Azhar UniversityCairo 11754Egypt

AIM:To detect the quantitative expression levels of the pro-inflammatory interleukin-8(IL8),antimicrobial peptides human beta defense-2(HBD2),and human beta defense-3(HBD3)genes in bacterial ***:The human conjunctival epithelial cells were obtained using the impression cytology technique from healthy controls and *** genes expression levels were determined utilizing a reverse transcription quantitative polymerase chain reaction(RT-q PCR).The contribution of causative agent type,the number of isolates and severity of clinical features,in the increase of genes expression was also ***:The RT-q PCR showed that IL8,HBD2,and HBD3 expression increased in bacterial conjunctivitis as compared to healthy control(Pelation between HBD2 up-regulation and HBD3 up-regulation was observed(Pelated to the up-regulation of IL8 and HBD2(Peleased with gram-negative bacteria compared to gram-positive ***3 is an obvious defender in different bacterial conjunctivitis.

关键词： interleukin-8 human beta defense-2 human beta defense-3 infectious conjunctivitis real-time polymerase chain reaction

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Acute kidney injury due to bilateral malignant ureteral obstruction:Is there an optimal mode of drainage?

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World Journal of Nephrology 2022年第6期11卷 146-163页

作者： Rabea ahmed Gadelkareem ahmed Mahmoud abdelraouf ahmed mohammed el-Taher abdelfattah Ibrahim ahmed Department of Urology Assiut Urology and Nephrology HospitalFaculty of MedicineAssiut UniversityAssiut 71515AssiutEgypt

There is a well-known relationship between malignancy and impairment of kidney functions,either in the form of acute kidney injury or chronic kidney *** the former,however,bilateral malignant ureteral obstruction is a surgically correctable factor of this complex *** warrants urgent drainage of the kidneys in emergency ***,there are multiple controversies and debates about the optimal mode of drainage of the bilaterally obstructed kidneys in these *** review addressed most of the concerns and provided a comprehensive presentation of this topic from the recent ***,we provided different perspectives on the management of the bilateral obstructed kidneys due to *** the frequent trials for improving the success rates and functions of ureteral stents,placement of a percutaneous nephrostomy tube remains the most recommended tool of drainage due to bilateral ureteral obstruction,especially in patients with advanced ***,the disturbance of the quality of life of those patients remains a major unresolved *** the unfavorable prognostic potential of the underlying malignancy and the various risk stratification models that have been proposed,the response of the kidney to initial drainage can be anticipated and evaluated by multiple renal prognostic factors,including increased urine output,serum creatinine trajectory,and time-to-nadir serum creatinine after drainage.

关键词： Acute kidney injury Kidney Malignancy Percutaneous nephrostomy Ureteral obstruction Ureter

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A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

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Computers, Materials & Continua 2023年第3期74卷 5087-5103页

作者： Al-Hussien Seddik mohammed Salah Gamal Behery ahmed el-harby ahmed Ismail Ebada Sokea Teng Yunyoung Nam Mohamed Abouhawwash Department of Computer Science Faculty of ScienceMinia UniversityMiniaEgypt Department of Computer Science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast Lansing48824MIUSA

The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its ***,researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it;this is called the stego *** paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response(QR)code and maze game image *** system consists of two *** first component contains two processes,encryption process,and hiding *** encryption process encrypts secret message bits in the form of a semi-QR code image whereas the hiding process conceals the pregenerated semi-QR code in the generated maze game *** the other hand,the second component contains two processes,extraction and decryption,which are responsible for extracting the semi-QR code from the maze game image and then retrieving the original secret message from the extracted semi-QR code image,*** results were obtained using the bit error rate(BER)*** results confirmed that the system achieved high hiding capacity,good performance,and a high level of robustness against attackers compared with other coverless steganography methods.

关键词： Coverless steganography data hiding information security QR code maze game

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Overlapping Shadow Rendering for Outdoor Augmented Reality

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Computers, Materials & Continua 2021年第5期67卷 1915-1932页

作者： Naira elazab Shaker el-Sappagh ahmed Atwan Hassan Soliman mohammed elmogy Louai Alarabi Nagham Mekky Faculty of Computers and Information Mansoura UniversityMansoura35516Egypt Universidade de Santiago de Compostela Santiago de Compostela15705Spain Faculty of Computers and Articial Intelligence Benha UniversityBenha13512Egypt Faculty of Computer Sciences and Information Technology Northern Border UniversityArarSaudi Arabia College of Computer and Information Systems Umm Al-Qura UniversityMeccaSaudi Arabiagham Mekky

Realism rendering methods of outdoor augmented reality(AR)is an interesting *** items in outdoor AR need advanced impacts like shadows,sunshine,and relations between unreal items.A few realistic rendering approaches were built to overcome this *** of these approaches are not dealt with real-time ***,the issue remains an active research topic,especially in outdoor *** paper introduces a new approach to accomplish reality real-time outdoor rendering by considering the relation between items in AR regarding shadows in any place during *** proposed method includes three principal stages that cover various outdoor AR rendering ***,real shadow recognition was generated considering the sun’s location and the intensity of the *** second step involves real shadow ***,we introduced a shadow production algorithm technique and shades through its impacts on unreal items in the *** selected approach’s target is providing a fast shadow recognition technique without affecting the system’s *** achieved an average accuracy of 95.1%and an area under the curve(AUC)of 92.5%.The outputs demonstrated that the proposed approach had enhanced the reality of outside AR *** results of the proposed method outperformed other state-of-the-art rendering shadow techniques’outcomes.

关键词： Augmented reality outdoor rendering virtual shadow shadow overlapping hybrid shadow map

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Sports Prediction Model through Cloud Computing and Big Data Based on Artificial Intelligence Method

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Journal of Intelligent Learning Systems and Applications 2024年第2期16卷 53-79页

作者： Aws I. Abu Eid Achraf Ben Miled Ahlem Fatnassi Majid A. Nawaz Ashraf F. A. Mahmoud Faroug A. abdalla Chams Jabnoun Aida Dhibi Firas M. Allan mohammed ahmed elhossiny Salem Belhaj Imen Ben Mohamed Faculty of Computing Studies Arab Open University Amman Jordan Computer Science Department Science College Northern Border University Arar Kingdom of Saudi Arabia Artificial Intelligence and Data Engineering Laboratory LR21ES23 Faculty of Sciences of Bizerte University of Carthage Tunis Tunisia Applied College Northern Border University Arar Kingdom of Saudi Arabia Faculty of Specific Education Mansoura University Mansoura Egypt

This article delves into the intricate relationship between big data, cloud computing, and artificial intelligence, shedding light on their fundamental attributes and interdependence. It explores the seamless amalgamation of AI methodologies within cloud computing and big data analytics, encompassing the development of a cloud computing framework built on the robust foundation of the Hadoop platform, enriched by AI learning algorithms. Additionally, it examines the creation of a predictive model empowered by tailored artificial intelligence techniques. Rigorous simulations are conducted to extract valuable insights, facilitating method evaluation and performance assessment, all within the dynamic Hadoop environment, thereby reaffirming the precision of the proposed approach. The results and analysis section reveals compelling findings derived from comprehensive simulations within the Hadoop environment. These outcomes demonstrate the efficacy of the Sport AI Model (SAIM) framework in enhancing the accuracy of sports-related outcome predictions. Through meticulous mathematical analyses and performance assessments, integrating AI with big data emerges as a powerful tool for optimizing decision-making in sports. The discussion section extends the implications of these results, highlighting the potential for SAIM to revolutionize sports forecasting, strategic planning, and performance optimization for players and coaches. The combination of big data, cloud computing, and AI offers a promising avenue for future advancements in sports analytics. This research underscores the synergy between these technologies and paves the way for innovative approaches to sports-related decision-making and performance enhancement.

关键词： Artificial Intelligence Machine Learning Spark Apache Big Data SAIM

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Cytokine profile in Egyptian hepatitis C virus genotype-4 in relation to liver disease progression

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World Journal of Gastroenterology 2005年第42期11卷 6624-6630页

作者： abdel-Rahman N Zekri mohammed S el-Din Ashour ahmed Hassan Hanaa M Alam el-Din Amal MR el-Shehaby Maha A Abu-Shady Virology and Immunology Unit Cancer Biology Department National Cancer Institute Cairo University Egypt Microbiology Department Faculty of Pharmacy Azhar University Egypt Microbiology and Immunology Department Sohag Faculty of Medicine South Valley University Egypt Virology and Immunology Unit Cancer Biology Department National Cancer Institute Cairo University Egypt Biochemistry Department el-Kaser el-Aini School of Medicine Cairo University Egypt

AIM： To observe the imbalance between T helper cell Th1 and Th2 cytokines in several chronic hepatitis disease at different stages of disease progression. METHODS： We measured the cytokine levels of Thl （IL-2 and IL-2R）, Th2 （IL-10） and the pro-inflammatory cytokines （IL-6 and IL-6R and TNF and TNF-RI and II） by the elISA technique in the sera of 33 hepatocellular carcinoma （HCC） patients and 20 chronic liver disease （CLD） patients. In addition, 20 asymptomatic hepatitis C virus carriers and 20 healthy subjects negative for hepatitis C virus（HCV） markers served as controls. RESULTS： Anti-HCV antibodies were found to be positive in 94% of HCC cases and 75% of CLD cases. On the other hand, HCV viremia was detected using RT- PCR in 67% of HCC cases and 65% of CLD cases. HBsAg was positive in 9% of HCC cases and 30% of CLD cases. Also bilharziaI-Ab was positive in 55% of HCC cases, 65% of CLD cases and in 70% of asymptomatic carriers （ASC）. HCC patients had significantly higher values of IL- 2R, TNF-RII （P〈0.001）, and TNF-RI （P〉0.05）, but lower TNFα （P〈0.001） and IL-6 （P = 0.032） in comparison to ASC. But, in comparison to non-cancer controls, HCC patients had higher values of IL-2R, IL-6R, TNF-RI and TNF-RII, but lower TNF-α （P〈0.001）. CLD patients had higher IL-2R, TNF-RI, and TNF-RII （P〈0.001） than ASC. But, in comparison to non-cancer controls, CLD patients had higher values of IL-2R, TNF-RI and TNF-RII, but lower TNF-α （P〈0.001）. IL-10 was higher （though not significantly） in HCC and CLD patients than in symptomatic carriers and non-cancer controls. CONCLUSION： Liver disease progression from CLD to HCC due to HCV genotype-4 infection is associated with an imbalance between Th1 and Th2 cytokines. IL-2R, TNF-RI, and TNF-RII could be used as potential markers.

关键词： Cytokine HCV Genotype-4 Liver disease

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Robust Multi-Output Machine Learning Regression for Seismic Hazard Model Using Peak Crust Acceleration Case Study,Turkey,Iraq and Iran

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地球科学学刊:英文版 2023年第5期34卷 1447-1464页

作者： Shaheen mohammed Saleh ahmed Hakan Guneyli Department of Geology College of ScienceKirkuk UniversityKirkuk 36001Iraq Department of Geology Faculty EngineeringCukurova UniversityBalcali-Adana 01330Turkey

This paper for the first time improved a Robust Multi-Output machine learning regression model for seismic hazard zoning of Turkey, Iraq and Iran using constructed 3-D shear-wave velocity(Vs), seismic tomography dataset model for the crust and uppermost mantle beneath the study area. The focus of this paper’s opportunity is to develop a scientific framework leveraging machine learning that will ultimately provide the rapid and more complete characterization of earthquake properties. This work can be targeted at improving the seismic hazard zones system ability to detect and associate seismic signals, or at estimating other seismic characteristics(crust acceleration and crust energy) while traditionally, methods cannot monitor the earthquakes system. This work has derived some physical equations for extraction of many variables as inputs for our developed machine learning model based on a reliable understanding of the tomography data to physical variables by preparing huge dataset from different physical conditions of crust. We have extracted the velocity values of the shear waves from the original NETCDF file, which contains the S velocity values for every one km of the depths of the crust for the study area from one km down to the uppermost mantle beneath the Middle East. For the first time, this study calculated new seismic hazard parameter called Peak Crust Acceleration(PCA) for seismic hazard analysis by considering the transmitted initial seismic energy through the Earthy wrote in python language ’s crust layers from hypocenter. All machine learning algorithms in this studusing anaconda platform the open-source Individual Edition(Distribution).

关键词： robust multi-output regressor tomography peak crust acceleration NETCDF machine learning hazards

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Identification and Classification of Crowd Activities

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Computers, Materials & Continua 2022年第7期72卷 815-832页

作者： Manar elshahawy ahmed O.Aseeri Shaker el-Sappagh Hassan Soliman mohammed elmogy Mervat Abu-elkheir Department of Information Technology Faculty of Computers and InformationMansoura UniversityEgypt Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems Faculty of Computers and Artificial IntelligenceBenha UniversityEgypt Faculty of Computer Science and Engineering Galala University435611SuezEgypt Department of Computer Science Faculty of Media Engineering and TechnologyGerman UniversityEgypt

The identification and classification of collective people’s activities are gaining momentum as significant themes in machine learning,with many potential applications *** need for representation of collective human behavior is especially crucial in applications such as assessing security conditions and preventing crowd *** paper investigates the capability of deep neural network(DNN)algorithms to achieve our carefully engineered pipeline for crowd *** includes three principal stages that cover crowd analysis ***,individual’s detection is represented using the You Only Look Once(YOLO)model for human detection and Kalman filter for multiple human tracking;Second,the density map and crowd counting of a certain location are generated using bounding boxes from a human detector;and Finally,in order to classify normal or abnormal crowds,individual activities are identified with pose *** proposed system successfully achieves designing an effective collective representation of the crowd given the individuals in addition to introducing a significant change of crowd in terms of activities *** results onMOT20 and SDHA datasets demonstrate that the proposed system is robust and *** framework achieves an improved performance of recognition and detection peoplewith a mean average precision of 99.0%,a real-time speed of 0.6ms non-maximumsuppression(NMS)per image for the SDHAdataset,and 95.3%mean average precision for MOT20 with 1.5ms NMS per image.

关键词： Crowd analysis individual detection You Only Look Once(YOLO) multiple object tracking kalman filter pose estimation

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