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تصفح المحتوي RDA
التصفح حسب الموضوعات
التصفح حسب اللغة
التصفح حسب الناشر
التصفح حسب تاريخ النشر
التصفح حسب مكان النشر
التصفح حسب المؤلفين
تصفح الهيئات
التصفح المؤتمرات
التصفح حسب نوع المادة
التصفح حسب العلاقة بالعمل
تم العثور علي : 4088
 تم العثور علي : 4088
  
 
إعادة البحث

Book 2012.
Mayesky, Mary.
ISBN: 9781111520977
372 التعليم الابتدائي   372.1 المدرسة الابتدائية  
Creative activities and seat work - Early childhood education - Child development
wadsworth,

Book 2003.
ISBN: 1863963308 :
745 الفنون الزخرفية   745.5 الأشغال اليدوية  
Handicrafts - Creative activities and seat work
ACP Publishing,

Book 2003.
ISBN: 1863963308 :
745 الفنون الزخرفية   745.5 الأشغال اليدوية  
Handicrafts - Creative activities and seat work
ACP Publishing,

Thesis 2024.
Abayzed, Esraa Ashor Abdelrehem.
610 الطب والعلوم الطبية   610 الطب والعلوم الطبية  
تصفح الوعاء  

Thesis 2024.
مخلوف ‘ الشيماء محمد السيد .
900 الجغرافيا والرحلات والتراجم والتاريخ   900 الجغرافيا والرحلات والتراجم والتاريخ   900 الجغرافيا والرحلات والتراجم والتاريخ  
Administrative development works to establish administrative systems and methods correctly in order to contribute to achieving progress in various fields. Administrative development is based on well-established and developed internal capabilities represented by a driving and growing economic ability - an interactive and participatory social ability - a conscious and directed political ability - and an administrative ability that provides modern technological means. Which seeks to raise the efficiency of work - get rid of regulations and rules that disrupt the workflow - work to achieve consistency and integration between specializations - so that the desired goals are achieved - and try to develop existing systems and introduce everything new in order to expand and develop.
Administrative development represents all administrative development efforts through training - consultation - field research - information and communications technology - e-government - and effective legislation to achieve balances among stakeholders in society.
Sustainable management in educational institutions is necessary to maintain a positive school culture - high morale among members of the school community - the participation of all members of the school community in setting the school’s vision and mission - and an important factor in determining the academic growth of students and the professional growth of members of the school community - and makes members of the school community their responsibility Shared - and is considered an important element in achieving long- and short-term goals. Sustainable management is based on the good practices of the educational institution and its competitiveness - and managing it in a sustainable manner to be a priority goal in all advanced educational policies. Official language schools are also among the educational institutions in Egypt that are located on It is responsible for educating students - and was established to meet the needs of a large sector of the Egyptian people who want to educate their children.
The study problem and its questions
The current situation of public language schools in Egypt indicates many problems with regard to the low performance of leadership and administrative work - the steps of school work - and the weakness of administrative development in terms of planning - organization - decision-making and oversight. Among the manifestations of this deficiency are the following

Articles 2023.
Ebrahim, Taghreed Ahmed.
362 خدمات المشاكل الاجتماعية  
Nursing Administration
Alexandria Scientific Nursing Journal /
Vol.25 (March 2023) /
Faculty of Nursing.

Thesis 2023.
AHMED ‘ ALAA ADEL EZAT .
900 الجغرافيا والرحلات والتراجم والتاريخ   900 الجغرافيا والرحلات والتراجم والتاريخ   900 الجغرافيا والرحلات والتراجم والتاريخ  
First and foremost - I express my gratitude to ALLAH for His assistance
and guidance throughout this thesis.
I would like to express my profound gratitude and sincere thankfulness to
Professor Abd Elnaby Kabeel for his continuous support and useful
suggestions throughout this research study. I would like to extend my
deepest appreciation to Assoc. Prof. Dr. Tamer Nabil for his invaluable
guidance - patience - encouragement - and support during the preparation of
this work. I am also grateful to Prof. Dr. Mohamed M. Khairat Dawood and
Assoc. Prof. Dr. Mohamed Abdelgaied for their continuous support - useful
suggestions - and encouragement.
I would like to thank Dr. Mohamed Mohamed Elsakka for his continuous
support to the end of this work.
I would like to express my heartfelt thanks to my family - especially my
father - mother - and my brother. Their love and unwavering support were
instrumental in the completion of this work.
Last but not least - I would like to thank my wife - my two daughters - and my
son for their support throughout my life.
II
Publications
Abdelgaied - M - Kabeel - A. E - Ezat - A. A - Khairat Dawood - M. M -
& Nabil - T. (2022). Performance improvement of the hybrid indirect
evaporative type air cooler and HDH desalination system using shell and
tube latent heat energy storage tank. Process Safety and Environmental
Protection - 168 - 800–809.
Kabeel - A. E - Ezat - A. A - Elsakka - M. M - Abdelgaied - M - Khairat
Dawood - M. M - & Nabil - T. (2022). Review of the Utilization of Heat
Transfer Equipment in Solar Humidification Dehumidification Systems. 1st
International Engineering Conference on Research and Innovation - First and foremost - I express my gratitude to ALLAH for His assistance
and guidance throughout this thesis.
I would like to express my profound gratitude and sincere thankfulness to
Professor Abd Elnaby Kabeel for his continuous support and useful
suggestions throughout this research study. I would like to extend my
deepest appreciation to Assoc. Prof. Dr. Tamer Nabil for his invaluable
guidance - patience - encouragement - and support during the preparation of
this work. I am also grateful to Prof. Dr. Mohamed M. Khairat Dawood and
Assoc. Prof. Dr. Mohamed Abdelgaied for their continuous support - useful
suggestions - and encouragement.
I would like to thank Dr. Mohamed Mohamed Elsakka for his continuous
support to the end of this work.
I would like to express my heartfelt thanks to my family - especially my
father - mother - and my brother. Their love and unwavering support were
instrumental in the completion of this work.
Last but not least - I would like to thank my wife - my two daughters - and my
son for their support throughout my life.
II
Publications
Abdelgaied - M - Kabeel - A. E - Ezat - A. A - Khairat Dawood - M. M -
& Nabil - T. (2022). Performance improvement of the hybrid indirect
evaporative type air cooler and HDH desalination system using shell and
tube latent heat energy storage tank. Process Safety and Environmental
Protection - 168 - 800–809.
Kabeel - A. E - Ezat - A. A - Elsakka - M. M - Abdelgaied - M - Khairat
Dawood - M. M - & Nabil - T. (2022). Review of the Utilization of Heat
Transfer Equipment in Solar Humidification Dehumidification Systems. 1st
International Engineering Conference on Research and Innovation

Thesis 2024
Elshouky ‘ Hadeer Hussein Abdel-Mawla Hassan .
621 الفيزياء التطبيقية   621.3 الهندسة الكهربية  
The use of image classification in medical fields is one of the most important uses - including skin cancer image classification. Skin cancer is a major health problem across the world - and early identification is critical for successful treatment. Skin cancer - which is defined by abnormal skin cell development - is a common and dangerous disease worldwide. Despite advances in digital diagnosis tools - many present skin cancer detection technologies frequently fail to attain adequate levels of accuracy. Disease detection - computer-aided diagnosis - and patient risk identification rely heavily on computer vision. This is particularly true for skin cancer - which may be lethal if not detected early on. Several computer-aided diagnosis and detection systems have already been developed to do this.
In this dissertation - two approaches for classifying skin cancer images were examined and compared with the proposed methods. Machine Learning (ML) and Deep Learning (DL) are these two approaches. ML approaches include Artificial Neural Networks - Support Vector Machines - Naïve Bayes - and Decision Tree. Both Convolutional Neural Networks and Pretrained Deep Neural Networks (PDNN) were employed in the DL approach.
Two methods for detecting and binary classifying dermoscopic skin cancer images into benign and malignant were proposed. The first proposed method employs K-Nearest Neighbor (KNN) as a classifier with several PDNN serving as feature extractors - (KNN-PDNN). These networks include AlexNet - VGG-16 - VGG-19 - EfficientNet-B0 - ResNet-18 - ResNet-50 - ResNet-101 - DenseNet-201 - Inception-v3 - and MobileNet-v2. The second proposed method employs some PDNN with the Improved Grey Wolf Optimizer (I-GWO) - (PDNN-I-GWO). The PDNN used in this technique are AlexNet - ResNet-18 - SqueezeNet - ShuffleNet - and DarkNet-19.
The experiments of KNN-PDNN method used 4000 images from the ISIC archive dataset to train and test images. In certain PDNN - the KNN-PDNN method’s accuracy exceeded 99%. The PDNN-I-GWO method investigated two datasets: MED-NODE and DermIS. The outcomes showed that the proposed methods outperformed the other tested approaches. The highest accuracy achieved by this method is 100% and 97% in the MED-NODE and DermIS datasets - respectively. The highest accuracy achieved with this method is 100% and 97% in the MED-NODE and DermIS datasets - respectively.
The dissertation consists of five chapters as follows:
Chapter 1: Introduction
An introduction to the dissertation is given - explaining the importance of the research point and the goals it seeks to achieve - and an explanation of the problems found in some of the old techniques that we seek to improve in this thesis and the extent of their impact on classifying skin cancer images. This chapter also summarizes what the other chapters contain and the order in which they are reviewed in the thesis.
Chapter 2: Literature Review
This chapter covers background on skin cancer image classification and presents some previous works and methods used and their features and characteristics.
Chapter 3: Proposed System
The third chapter presents the proposed algorithms that were represented and applied in the dissertation. It reviews them in detail and discusses the additions and modifications that were made to achieve high accuracy. This chapter also presents the preprocessing of images before using them in the proposed methods. In addition - it includes different datasets for training and testing images.
Chapter 4: Experimental Results
It reviews all the experiments - their accompanying results - and details of the images that were used in the experiments. This dissertation also includes many comparisons between the proposed and modified algorithms that were used during the image classification process. This included using several methods and methods to evaluate and compare the performance of these algorithms.
Chapter 5: Conclusions and Recommendations for Future Work
It presents a summary of the results reached as well as some recommended points for future work that can be used to develop the work presented in this dissertation or related works - The use of image classification in medical fields is one of the most important uses - including skin cancer image classification. Skin cancer is a major health problem across the world - and early identification is critical for successful treatment. Skin cancer - which is defined by abnormal skin cell development - is a common and dangerous disease worldwide. Despite advances in digital diagnosis tools - many present skin cancer detection technologies frequently fail to attain adequate levels of accuracy. Disease detection - computer-aided diagnosis - and patient risk identification rely heavily on computer vision. This is particularly true for skin cancer - which may be lethal if not detected early on. Several computer-aided diagnosis and detection systems have already been developed to do this.
In this dissertation - two approaches for classifying skin cancer images were examined and compared with the proposed methods. Machine Learning (ML) and Deep Learning (DL) are these two approaches. ML approaches include Artificial Neural Networks - Support Vector Machines - Naïve Bayes - and Decision Tree. Both Convolutional Neural Networks and Pretrained Deep Neural Networks (PDNN) were employed in the DL approach.
Two methods for detecting and binary classifying dermoscopic skin cancer images into benign and malignant were proposed. The first proposed method employs K-Nearest Neighbor (KNN) as a classifier with several PDNN serving as feature extractors - (KNN-PDNN). These networks include AlexNet - VGG-16 - VGG-19 - EfficientNet-B0 - ResNet-18 - ResNet-50 - ResNet-101 - DenseNet-201 - Inception-v3 - and MobileNet-v2. The second proposed method employs some PDNN with the Improved Grey Wolf Optimizer (I-GWO) - (PDNN-I-GWO). The PDNN used in this technique are AlexNet - ResNet-18 - SqueezeNet - ShuffleNet - and DarkNet-19.
The experiments of KNN-PDNN method used 4000 images from the ISIC archive dataset to train and test images. In certain PDNN - the KNN-PDNN method’s accuracy exceeded 99%. The PDNN-I-GWO method investigated two datasets: MED-NODE and DermIS. The outcomes showed that the proposed methods outperformed the other tested approaches. The highest accuracy achieved by this method is 100% and 97% in the MED-NODE and DermIS datasets - respectively. The highest accuracy achieved with this method is 100% and 97% in the MED-NODE and DermIS datasets - respectively.
The dissertation consists of five chapters as follows:
Chapter 1: Introduction
An introduction to the dissertation is given - explaining the importance of the research point and the goals it seeks to achieve - and an explanation of the problems found in some of the old techniques that we seek to improve in this thesis and the extent of their impact on classifying skin cancer images. This chapter also summarizes what the other chapters contain and the order in which they are reviewed in the thesis.
Chapter 2: Literature Review
This chapter covers background on skin cancer image classification and presents some previous works and methods used and their features and characteristics.
Chapter 3: Proposed System
The third chapter presents the proposed algorithms that were represented and applied in the dissertation. It reviews them in detail and discusses the additions and modifications that were made to achieve high accuracy. This chapter also presents the preprocessing of images before using them in the proposed methods. In addition - it includes different datasets for training and testing images.
Chapter 4: Experimental Results
It reviews all the experiments - their accompanying results - and details of the images that were used in the experiments. This dissertation also includes many comparisons between the proposed and modified algorithms that were used during the image classification process. This included using several methods and methods to evaluate and compare the performance of these algorithms.
Chapter 5: Conclusions and Recommendations for Future Work
It presents a summary of the results reached as well as some recommended points for future work that can be used to develop the work presented in this dissertation or related works

Thesis 2024.
Abd Elghafar, Walaa Tokal Mohammed.
362 خدمات المشاكل الاجتماعية  
Nursing Administration
تصفح الوعاء  

Thesis 2024.
Safaan, Eman Yasser Mousa.
613 الرعاية وتعزيز الصحة  
Helping behavior - Quality of work life
تصفح الوعاء  


من 409
 







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