Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

This article explores the process of VGI collection by assessing the relative usability and accuracy of a range of different methods (Smartphone GPS, Tablet, and analogue maps) for data collection amongst different demographic and educational groups, and in different geographical contexts. Assessments are made of positional accuracy, completeness, and data collectors’ experiences with reference to the official cadastral data and the administration system in a case-study region of Iraq. Ownership data was validated by crowd agreement. The result shows that successful VGI projects have access to varying data collection methods.

This research aims at identifying the Iraqi EFL students' academic buoyancy in reading and listening skills and then finding out the difference between the two skills; Furthermore, finding out the five predictors differences of each of the two scales. Two academic buoyancy scales used to collect data. After achieving the scales' psychometric characteristics, they are submitted to the study sample. The sample of (100) female students selected according to the stratified random method from the second class at the Department of English\ College of Education for Women\ University of Baghdad. The results show that the students have academic reading buoyancy and have not academic listening buoyancy; the difference between the two abilities shows

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

Welcome to International Journal of Research in Social Sciences & Humanities (IJRSSH). It is an international refereed journal of Social Sciences, Humanities & Linguistics in English published quarterly, both print and online.

Infographics have the capability to organize and display information in a way that is easy for viewers to retrieve and make observations. While infographics have been successful in various fields, their potential benefits in composition writing have not been explored. The primary objective of this study is to investigate the perspectives of Iraqi EFL students who used infographics as an educational technology tool in composition writing, and to identify how gender influences students’ performance when using infographics in EFL writing classes. The significance of this study lies in its integration of infographics as an educational technology tool for teaching writing, aligning with the current trend of technology integration in educati

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In recent years, with the growing size and the importance of computer networks, it is very necessary to provide adequate protection for users data from snooping through the use of one of the protection techniques: encryption, firewall and intrusion detection systems etc. Intrusion detection systems is considered one of the most important components in the computer networks that deal with Network security problems. In this research, we suggested the intrusion detection and classification system through merging Fuzzy logic and Artificial Bee Colony Algorithm. Fuzzy logic has been used to build a classifier which has the ability to distinguish between the behavior of the normal user and behavior of the intruder. The artificial bee colony al