Today, with the development of technologies to capture and share images, the number of digital images has increased significantly. The management of this volume of images requires an efficient system to review, classify, search and retrieve the images. New generations of image retrieval systems usually take one or a few keywords from the user to retrieve images with visual content related to that keywords. A mechanism that can automatically describe the content of an image (like a human) can increase the efficiency of these systems. Automatic Image Annotation or AIA is a professional method to express the content of images by keywords or tags. AIA systems, investigate the relationship between the meaning of a text and low-level image features by using machine learning techniques. They automatically assign some tags to images to facilitate fast search based on image contents. In this paper, we explain the different steps to implement an AIA system, review the related works and express the problems and challenges in designing such systems. We also introduce several datasets suitable for AIA systems.

This article, with a historical approach, deals with geographical sources and traces their formation from the oldest time. Next, the causes of Moslim's attention to geography and their first written works are discussed. The most famous works are mentioned, annatated, and described. Then, follows a classification of geographical sources and the introduction of some of the electronic ones in English considered to be the most important works in this discipline. The author believes that the geographical researchers, should at least be acquainted with Farsi-Arabic printed sources of the discipline described in most of the Persian reference guides.For each source, the bibliographic data, its scope, the method of accessibility, the way of making contact with the publisher and ordering system, its price and other data and services are provided. Five sources of this kind are described in detail and samples of their entries and contents are given.

Image annotation systems are responsible for describing the content of the images by assigning tags to them. The purpose of this research is to improve the accuracy and speed of image annotation system. Recently, with the growing of images, the image annotation process is based on the basics of images instead of themselves. One of these new methods is the implementation of the non-negative matrix algorithm (NMF) on the features of the images. In the proposed method, for the first time, in order to increase the speed and efficiency of the7 system, we use a method that called the block principal pivoting for the NMF solution. This method has ability to add online new class of data to its knowledge and knowledge learning in a compact form. Moreover, the ability to train based on received data without having to be re-processed. In the training phase, the matrix of the coefficients and the base of the input images are obtained using the Block Principal Pivoting method. Then, at the test phase for the input image, by extracted features of the image and the coefficients obtained from the training phase, the coefficient of belonging to the test image is calculated to each of the classes of training images. Then, this coefficient while searching among the teaching images for assigning the label to test image increases the accuracy of the algorithm. This search is done by the KNN method on the base of the images. To test the proposed method, we used two databases Corel5K and real animal data (derived from 500px) and, finally, compared with existing methods, which we found in the Corel5K database at a precision of 50. 20 and real data was 62. 89. Precision have been increased considerably.

This article studies and reviews the explication of some lines in Persian literary texts. Presenting some reasons and evidence, the author mentions some mistakes made by explicators in narrating these lines and endeavors to clearly explicate them. Considering the explication and narration of these lines makes it necessary to pay attention to the surface structure of these works.

Crude oil is an energy resource that mostly is composed of the hydrocarbons and trace corrosive compounds as well has found some cruxes in the petroleum refining industry because of the vast applications of the different types of metals. There is expectation to investigate the effect of two different types of crude oils on the corrosion of seven types of the selected ferrous metals in the pertinent research. The concerned corrosive properties of both crude oils have tested by standard methods and instruments, also the chemical compositions of the selected ferrous metals have tested. The corrosion rates of a series of the similar size prepared metal coupons have tested after limited immersion time periods as three trials in crude oils by the weight loss method since aiding the microscopic analysis to identify the corrosion compounds. Apart from those speculations, the decayed metallic elemental mounts from the metals into crude oils and the reductions of the initial hardness of metal coupons have tested. The obligatory results shows the relatively higher corrosion rates from carbon steels, relatively lower corrosion rates from stainless steels in both crude oils, formation of FeS in most of observations, decay of ferrous and copper into crude oils from some metals, and slight reductions of the initial hardness of metal coupons due to the formation of the corrosion on the metal surfaces.

1. Introduction: Persian literature is one of the most prolific literatures in the world, in such a way that Persian poets and writers have left amazing works for the future. One of these outstanding works is the valuable book Nafsat al-Masdour. Its author is "Shahab al-Din Mohammad Ibn Ahmad Monshy Khorandzi Zaidari Nesawi, the secretary of Soltan Jalal alDin Kharazmshah" (Safa, 1986: 3/246). Zaidari Nesawi, the owner of Kharazmshah's essay, has witnessed many events and atrocities of the Mongols at first hand. On the other hand, his existence is full of poetic feelings,for this reason, he has left such a legacy that not only those who are interested in history, but also scholars of Persian literature, have benefited from reading it. . .

Automatic image annotation refers to automatically assignment of textual labels according to visual content of images. Althoughin the last decade great deal of research has been done in this area, Butbecause of numerous labels and semantic gap between the labels and the low-levelvisualfeatures, the accuracy and efficiency of these systems is reduced. In this study, an annotation method is proposed using two-level clustering based on featureswhich are reduced with genetic algorithm and as well as semantics. Clustering makes visual similar images and also semantic related images be placed next toeach otherandbe annotated. This leads to fast annotation and also has an acceptable performance for an annotation system. To evaluate the proposed method, two well-known datasets, Corel5k and IAPR TC-12 are selected. The results show acceptable performance of the proposed method in comparison with other methods.

Ontology population refers to extracting the instances of classes (concepts) of an ontology from text. On the other hand Semantic Web provides structured content by adding annotations to documents. Semantic annotation tags class instances and map them into classes in an ontology. Thus annotation and population are two sides of a coin. This paper introduces an inter-language population and annotation system called POPTA. It annotates Persian texts according to an English ontology and populates the English ontology by instances extracted from Persian texts. POPTA exploits a combination of statistical and pattern based approaches besides web based methods, search engines, online encyclopedia and Wikipedia to perform the annotation and population tasks.