Abstract : The research focuses on the analyzing and measuring the suitability of environmental governance mechanisms and functional management, as well as how they relate to the availability of environmental resources and the demands of environmental sectors in a certain time limit. It also examines investment priorities in order to stimulate the effective operation of services at the local and regional levels, including the functional role, and applies these to one of the new cities to assess how compatible policies are for managing and directing urban growth for the new city of Fayoum. The study extracted certain variables pertaining to environmental governance systems for cities, particularly new cities, by means of an investigation of global experiences. Through a questionnaire for experts to create these indicators and apply them on Egypt, the research examined the appropriateness of these indicators for the Egyptian new Fayoum city, The group of indicators was determined in bundles that would boost the project's effectiveness. Effective administration of emerging cities using environmental governance metrics and frameworks..
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Abstract : Multiple methods for classifying rice seeds were developed because of the time and effort involved in manually observing rice seeds. In light with this, machine learning has been found to be an effective method for seed classification. The goal of this paper is to determine a better classifier using WEKA Machine Learning Algorithms for rice seed classification in terms of rate of accuracy and training time. To do this, data mining technique was done since agriculture has been a clear focus of big data efforts. The tool used for data mining is WEKA, a collection of machine learning algorithms for data mining tasks. Data preparation, classification, regression, clustering, mining of association rules, and visualization are all included in this package. Among the 23 classifiers used to classify rice seeds, the Random Tree Classifier achieved a 100% accuracy and training time of 0.02 seconds, hence the mentioned machine learning algorithm was proven effective in providing a perfect accuracy rate and shorter period of training time..
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Abstract : Due to the significant rise in the number of private automobiles for several decades, numerous transportation-related matters have worsened very quickly. The most affected areas are those designed for pedestrians basically, such as downtown and historical cores. Recently, pedestrianization has been promoted as a feasible trend to promote sustainable social and economic growth in such urban communities. The lead in this trend was for European and American cities, but there was success in applying this approach in some cases and failure in others, which is mainly due to the wrong choice of the area suitable for applying the approach in terms of its urban, social and environmental conditions. Many towns and municipalities around the world want to make parts of their central districts pedestrianized, but they lack the means and expertise to carry out a comprehensive feasibility assessment of the project before starting it to avoid its failure after implementation. This study aims to create an initial index that can help local governments to identify the appropriation of a district for pedestrianization. This index aims to identify and reject unfeasible candidate districts early on, allowing resources to be redirected toward developing more effective plans for districts deemed more suitable for pedestrianization. The index will be developed based on a literature review, followed by a comparative and analytical study of several successful international case studies. To make the index quantitative, the scoring system for the index criteria will be done through statistical analysis to determine the relative importance degree of each criterion. So, the research result will be a quantitative initial index to determine a district's suitability for pedestrianization schemes..
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Abstract : Retinal fundus imaging plays a vital role in the early diagnosis of retinal diseases such as glaucoma, diabetic retinopathy, and cataracts. However, image quality is often compromised by specular reflections caused by flash photography, leading to reduced diagnostic accuracy. This study proposes a hybrid model for glaucoma detection that combines a preprocessing stage to remove specular reflections with an advanced segmentation phase utilizing a modified Convolutional Neural Network (CNN) architecture, specifically based on AlexNet. The preprocessing phase extracts diffuse and specular components using seven methods, and the best quality output is passed through a high-emphasis filter. The segmented images are then processed in the feature extraction phase, followed by classification using a Support Vector Machine (SVM) with multiple kernel options. This model aims to improve the accuracy of glaucoma detection, overcoming limitations posed by image artifacts and providing a robust solution for retinal disease screening. The hybrid CNN-AlexNet model enhances detection capabilities, ensuring better image quality and higher classification accuracy, making it an effective tool for early glaucoma diagnosis. Experimental results demonstrate that the proposed model achieves significant improvements in preprocessing, the performance parameters are 0.961, with the glaucoma detection phase shows an accuracy of 94.83%, sensitivity of 94.19%, specificity of 96.37%, and an area under the receiver operating characteristic curve (AUROC) of 0.99.1..
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Abstract : This paper aims to analyze the scientific production of the Urban Competitiveness and National Urban Policy research fields to identify research topics and publication patterns. Accordingly, bibliometric analysis was selected as a quantitative meta-analysis literature review method. Scopus was the main database for extracting the scientific production in Urban Policy and Competitiveness. Various bibliometrics analysis techniques were used to analyze 59 and 326 publications on Urban Competitiveness and urban policy, respectively. The main results are summarized as follows: (i) the number of publications on Urban Competitiveness has increased significantly, and (ii) contrarily, relatively urban policy literature is concerned with competitiveness despite its significant role in Urban Planning Policy..
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