This paper presents, a hybrid method, low-resolution and high-resolution, for Persian page segmentation. In the low-resolution page segmentation, a pyramidal image structure is constructed for multiscale Analysis and segments Document image to a set of regions. By high-resolution page segmentation, by connected components Analysis, each region is segmented to homogeneous regions and identifying them as texts, images, and tables/drawings. The proposed method was experiment with the Persian Documents. The result of these tests have shown that the proposed method provide more accurate and speed results.

In this paper we present Document Analysis and classification system to segment and classify contents of Arabic Document images. This system includes preprocessing, Document segmentation, feature extraction and Document classification. A Document image is enhanced in the preprocessing by removing noise, binarization, and detecting and correcting image skew. In Document segmentation, an algorithm is proposed to segment a Document image into homogenous regions. In Document classification, Neural Network (Multilayer Perceptron-Back propagation) classifier is applied to classify each region to text or non text based on a number of features extracted in feature extraction. These features are collected from different other researchers’ works. Experiments were conducted on 398 Document images selected randomly from printed Arabic text database (PATDB) which was selected from various printing forms which are advertisements, book chapters, magazines, newspapers, letters and reports Documents. As results, the proposed segmentation algorithm achieved only 0. 814% as ratio of the overlapping areas of the merged zones to the total size of zones and 1. 938% as the ratio of missed areas to total size of zones. The features, that show the best accuracy individually, are Background Vertical Run Length (RL) Mean, and Standard Deviation of foreground.

INTRODUCTION: Well-established guidelines and standards are essential for effective disaster management and relief operations. The aim of this study was to review the existing Documentation in Red Cross and Red Crescent Societies regarding disaster relief guidelines. METHODS: This narrative review was conducted using a Documentary research method in 2023. In order to find articles related to standardization of relief and recommendations, extensive searches were conducted in relevant databases, with a special emphasis on the International Federation of Red Cross and Red Crescent Societies (IFRC) database. The identified Documents were analyzed using Document Analysis and classification techniques. FINDINGS: The most important point in the IFRC review was that the guidelines are divided into two parts: general and specific. It is not necessary to use general guidelines, but specific guidelines are important. IFRC guidelines are usually developed in cooperation with the 190 member states. However, it is recommended that each country adapt these guidelines to its own specific circumstances. CONCLUSION: The results showed that when it comes to specialist areas such as housing and aid workers safety, IFRC recommendations are a valuable resource for countries when developing and updating national disaster relief protocols. While the IFRC principles provide a useful starting point, their successful use requires careful review and modification to meet the unique local conditions and requirements of each country.

BACKGROUND: The family physician plan formed at the heart of the health system can play a vital role in the results and the optimal cost of resources. Social marketing is a process that uses the basics and principles of commercial marketing in the field of health to develop and implement a health plan. This study seeks to analyze the Documents related to the program from the perspective of social marketing components. MATERIALS AND METHODS: This qualitative Document Analysis study was conducted in 2021 by reviewing the Documents and content of the texts related to family physician plan. The obtained data were analyzed by the directed content Analysis method after extraction and collection. RESULTS: The results showed the identification of social marketing components in the family physician plan. However, the two most essential parts of “insight” and “behavior theory, ” which address the underlying issues in an intervention, were not found in the analyzed Documents and texts. CONCLUSION: It is necessary to use a coherent and appropriate approach to revise and develop the family physician plan. To resolve the current challenges and problems of the family physician plan, the application of components and the social marketing approach that addresses all the required aspects of a health plan is a suitable model and approach.

This study aimed to examine the policies in the Iranian English for Academic Purposes (EAP) education and the extent to which objectives match the policies and are materialized in practice. To this end, course descriptions in the syllabi for the EAP programs were evaluated through Document Analysis and triangulated with the experts’ perspectives through interviews to examine the current status of EAP policy-making and practice in Iran. Seven policy areas from Kaplan and Baldauf’ s (2005) language-in-education planning were chosen as the framework of the study. Based on Document Analysis and interviews with the experts, the similarities and discrepancies in micro and macro levels were investigated. The results showed that EAP course descriptions do not include any comments on policy and there were discrepancies in policy and practice due to such factors as lack of communication channel between the EAP stakeholders and policy-makers. Finally, the study revealed that due to deficiencies in both policy and practice and in order to reach an acceptable status, EAP programs are in dire need for reconceptualizing policy-making and practice. The findings of this study have significant implications for EAP policies and practice in the academic system of Iran.