Detection of textual data from scene text images is a very thought-provoking issue in computer graphics and visualization. The challenges of text detection come from the nature of images used to detect text from them. The technology proposed is comprised of three main stages: Blurring, transformation to the frequency domain, and de-blurring in the frequency domain as preprocessing procedures; a proposed hybrid model for text detection using k-means clustering and text bounding boxes is used, and (CNN) framework used to classify into textual and non-textual regions. We used the Stroke Width Technique (SWT) when increasing the value of k by analyzing the width of the strokes in the image and thus reducing the potential textual regions resulting from the MSER, which leads to reducing the time and increasing the accuracy of detection, a convolutional neural network (CNN) algorithm is used to perform a classification of all bounding boxes. For the suggested technique's evaluation, results are collected on three popular datasets, including SVT, IIIT5K, ICDAR 2013, and ICDAR 2015. The datasets for SVT, IIIT5K, ICDAR 2013, and ICDAR 2015 each have classification results of 87.41.

The education process, which includes teachers and students, as well as the teaching environment in general, has drawn the attention of the education process due to desirable characteristics such as the educational function, which is distinguished by evolution in its performance methods, scalability, coherence, cost savings, and efficiency. Over the last several decades, e-teaching has varied from the traditional education style, where teachers encounter many difficulties while implementing the traditional education style. Researchers have arrived at conclusions regarding the variables that influence teachers’ acceptance of e-teaching by asking respondents to fill out questionnaires, conduct interviews, collect relevant information, and analyze the data obtained. In addition, colleges and universities have been searching for innovative ways to make education readily available to learners and make teaching easier for teachers. Despite the great importance of e-teaching in Iraq to support higher education and human development in contemporary ways, the implementation of e-teaching resists multiple challenges in Iraq. The proposed work can summarize these challenges as the few lecturers and trainers who provide training courses in preparing electronic lectures, information and communications technology infrastructure, electronic lectures and educational materials, tutors, and technical expertise. This paper aimed to identify factors determining the effect of activating e-teaching in Iraq. The research will elaborate on the concept of e-teaching in Iraq and discuss its importance and impacts with significant emphasis on Iraq. The current work concludes that e-teaching in Iraq has made meaningful progress in three universities.

Wireless Mesh Networks (WMNs) provide seamless connectivity in rapidly changing and dense environments. But when gateways are integrated to provide network access from outside the current topology, several issues become problems. These include maintaining high levels of performance, energy efficiency, security awareness and interconnection. Traditional routing protocols such as Ad hoc On-Demand Distance Vector Routing (AODV) were not able to achieve these two purposes at all in a hybrid setting where efficient communication with the gateway was needed, especially when faced with high mobility, node density and changing traffic loads. This paper introduces that the problem can be resolved by implementing Fuzzy Control Energy Efficient (FCEE) routing in WMNs The FCEE routing method, characteristic innovative energy-efficient real-time failure mechanism and overall network performance enhancement for wireless mesh networks By integrating fuzzy logic into the AODV framework, the FCEE method adds a short-term memory module that optimizes packet broadcasts based on real-time levels of energy available to each node. The FCEE method not only enhances decision-making for packet forwarding but also reduces unwanted broadcasts thus extending the life of the entire network. Simulations show the FCEE performs better than traditional methods in terms of both energy efficiency, congestion control, and adaptability to dynamic situations. The proposed method thus provides an affordable way to improve the operation of wireless mesh networks, particularly in the case of high traffic areas or long periods where resources are constrained.