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Assessment and Distribution of Heavy Metals Pollutants in Manzala Lake, Egypt

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Journal of Geoscience and Environment Protection 2015年第6期3卷 107-122页

作者： mahmoud abd el-kawy zahran Yasser Ahmed el-Amier abdelhamid Ahmed elnaggar Hoda abd el-Azim Mohamed Muhammad abd el-Hady el-Alfy Botany Department Faculty of Science Mansoura University Mansoura Egypt Soils Department Faculty of Agriculture Mansoura University Mansoura Egypt Marine Pollution Department National Institute of Oceanography and Fisheries Suez Egypt

Contamination with heavy metals is one of the most serious problems in the aquatic environments. In Egypt, Manzala Lake is suffering from this problem. The objective of this work was to assess heavy metals pollutants and their spatial distribution in Manzala Lake using GIS technique. Georeferenced water and sediment samples were randomly collected from the lake. The detected heavy metals were: Fe, Pb, Cu, Cd, Cr, Zn and Co. The obtained results indicated that the highest concentrations of heavy metals were observed in the northeastern and the southern parts of the lake nearby drains. This could be attributed to industrial, agricultural and municipal wastes coming through the drains especially Bahr el-Baqar drain and the industrial wastes coming from Port Said drains. From the geo-accumulation index, it was noticed that the lake is more polluted with cadmium and lead in the hydrosoils samples. All metals in water are within the EPA standard limit except for cadmium. Geostatistics provides effective methods to quantify the contaminated waters and sediments which support decision-making about redevelopment scenarios or remediation techniques.

关键词： Manzala Lake Heavy Metals Indices Pollution GIS

Efficient Deep CNN Model for COVID-19 Classification

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Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： Walid el-Shafai Amira A.mahmoud el-Sayed M.el-Rabaie Taha E.Taha Osama F.zahran Adel S.el-Fishawy Mohammed abd-elnaby Fathi E.abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection was initially acknowledged as a global pandemic in Wuhan in *** Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death *** X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis *** are numerous ways to identify positive COVID-19 *** of the fundamental ways is radiology imaging through CXR,or CT *** comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high ***,automated classification techniques are required to facilitate the diagnosis *** Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical *** deep Convolutional Neural Networks(CNNs)can learn and extract essential features from different medical image *** this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is *** activation functions as well as three optimizers are tested and compared for this *** proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train *** performance is tested and investigated on the CT and CXR *** activation functions:Tanh,Sigmoid,and RelU are compared using a constant learning rate and different batch *** optimizers are studied with different batch sizes and a constant learning ***,a comparison between different combinations of activation functions and optimizers is presented,and the optimal configuration is ***,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early *** proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset with training times of 58 min and 46 min on CXR an

关键词： COVID-19 image classification CNN DL activation functions optimizers

Hybrid Segmentation Approach for Different Medical Image Modalities

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Computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid el-Shafai Amira A.mahmoud el-Sayed M.el-Rabaie Taha E.Taha Osama F.zahran Adel S.el-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

Efficient Segmentation Approach for Different Medical Image Modalities

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Computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid el-Shafai Amira A.mahmoud el-Sayed M.el-Rabaie Taha E.Taha Osama F.zahran Adel S.el-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

A Note on L-double Gradation Fuzzy Topological and L-double Fuzzy Closure Spaces

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模糊系统与数学 2010年第3期24卷 53-61页

作者： A.M.zahran M.Azab abd-Allah Kamal el-Saady A.Ghareeb Mathematics Department Faculty of ScienceTaibah University Department of Mathematics Faculty of ScienceAssuit university Department of Mathematics Faculty of ScienceSouth Valley University

We prove the existence of both final L-double gradation fuzzy topological spaces and final L-double fuzzy closure spaces. From this fact,we define and study the notions of the L-double quotient spaces and the sum of L... 详细信息

关键词：模糊理论计算方法 “L-double Fuzzy” 数学理论

Deep CNN Model for Multimodal Medical Image Denoising

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Computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid el-Shafai Amira A.mahmoud Anas M.Ali el-Sayed M.el-Rabaie Taha E.Taha Osama F.zahran Adel S.el-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the RelU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

Morphological and molecular characterization of fungus isolated from tropical bed bugs in Northern Peninsular Malaysia, Cimex hemipterus(Hemiptera: Cimicidae)

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Asian Pacific Journal of Tropical Biomedicine 2015年第9期5卷 684-690页

作者： abdul Hafiz Ab Majid Zulaikha zahran abd Hafis abd Rahim Nor Azliza Ismail Wardah abdul Rahman Kartiekasari Syahidda Mohammad Zubairi Hamady Dieng Tomomitsu Satho Household and Structural Urban Entomology Laboratory School of Biological Sciences Universiti Sains Malaysia Plant Pathology Laboratory School of Biological Sciences Universiti Sains Malaysia Institute of Biodiversity and Environmental Conservation Universiti Malaysia Sarawak Department of Microbiology Faculty of Pharmaceutical Sciences Fukuoka University

Objective:To investigate some morphological and molecular characteristics of fungal parasites isolated from wild tropical bed bug, Cimex ***: A series of culture methods were used to obtain fungal isolates from i eld-collected bed bugs. Characteristics of the isolates such as colony appearance, mycelial texture and pigmentation were studied to explore their morphology. Isolates were also subjected to a PCRbased genotyping ***: There were noticeable dif erences in morphological characteristics among the four isolates. Conidial areas of one isolate were dark green, whereas those of the remaining colonies were olive-green, black or dark brown. Conidia of the dark green isolate were globose, while those of olive-green, black and dark brown isolates were globose to subglobose, globose to spherical and globose to subglobose/i nely roughened, respectively. These morphological specii cities and the molecular analyses showed that the fungal internal transcribed spacer ribosomal region and β-tubulin gene sequences of the isolates shared clade with Trichoderma and Aspergillus ***: Overall, the new discovery of common pathogens in agricultural i eld developed in live bed bugs storage tank may initiate the use of biological agents in later years.

关键词： Cimex hemipterus Aspergillus Trichoderma β-tubulin Internal transcribed spacer Morphological characteristics

Assessment of Standard Criteria Implementation in Heamodialysis Water Treatment Units in Sharkia Governorate

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Open Journal of Nephrology 2021年第2期11卷 133-143页

作者： Said Sayed Ahmed Khamis Asmaa M. el-Dardery Ahmed Mohamed zahran Zeinab abdel Aziz Kasemy Azza abd el-Monsef Gomaa Ministry of Health El-Sharkia Egypt Department of Internal Medicine & Nephrology Faculty of Medicine Menoufia University Al Minufya Egypt Department of Public Health and Community Medicine Faculty of Medicine Menoufia University Al Minufya Egypt

Introduction: Haemodialysis is the most well-established form of treatment for ESRD. Method: To evaluate the implementation of standard criteria in heamodialysis water treatment units in Sharkia governorate and to determine the weak points in application of standard criteria, and reach the optimal standards to improve pt. outcomes, across the sectional study was conducted at 30 heamodialysis units of Sharkia governorate, using a modified questionnaire was developed based on MOH protocol and international guidelines such as CARI guidelines, AAMI guidelines and others by the researchers. All data were collected, tabulated and statistically analyzed using SPSS 22.0 for windows (SPSS Inc., Chicago, IL, USA). Results: Of the 30 units, the majority more than 80% of the units achieved the infrastructure and schematic structure, contain water purification devices, good infection control policies, proper chemical disinfection, good monitoring and quality control, accepted maintenance technician evaluation and collected processed water samples results matched decree of 63 for 1996. Conclusion: Most of the studied units nearly fulfilled the standard specifications of both MOH and AAMI. Ensuring that water quality meets AAMI standards and recommendations will minimize patient exposure to potential contaminants such as chemical hazards and endotoxemia associated with the use of the treated water for HD.

关键词： Water Purification Pyrogenic Reactions Reverse Osmosis (RO)

Antiphospholipid Syndrome: Nephrologists’ Perspective

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Open Journal of Internal Medicine 2020年第2期10卷 112-120页

作者： Noha abdou Sabry abd Allah Shoeib Enas Sobhy zahran Shebin el Kom Teaching Hospital Shebin El Kom Egypt Faculty of Medicine Menoifya University Monufia Egypt

Introduction: Antiphospholipid antibody syndrome is a complex autoimmune disease that can affect all systems of the body and characterized by presence of antiphospholipid antibodies that cause vascular thrombosis and pregnancy complications, kidney involvement is very common in patients with antiphos- pholipid syndrome and leads to many serious complications. Objectives: study the effect of antiphospholipid syndrome on kidneys. Data Sources: By searching and reviewing Medline databases (Pub Med and Medscape) and all renal involvement in antiphospholipid syndrome materials available till 2019. Study Selection: All studies were independently assessed for inclusion. They were included if they fulfilled the following criteria: 1) published in English language;2) published in peer-reviewed journals;3) discussed the involvement of kidney in antiphospholipid syndrome. Data Extraction: Data from each eligible study were independently abstracted using a data collection form to capture information related to our concerned study outcomes. If the studies did not fulfill the inclusion criteria, they were excluded. Study quality assessment includes if ethical approval is gained, eligibility criteria specified, adequate information and defined assessment measured. Data Synthesis: Structured review with the results tabulated was made for comparison. Conclusions: We can conclude that kidney affection in patients with antiphos- pholipid syndrome has a wide spectrum and variation.

关键词： Antiphospholipid Syndrome Kidney Nephropathy Thrombosis aPL