The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The study introduces the twentieth century background where the image of teacher is shaped by various factors according to the wide emergence of new educational institutions in the aftermath of the Second World War. A group of writers mirrored the influence of the war on educational institutions and accordingly on the image of teacher in their novels whose main action is set in and around the campus of a university. The genre dates back to the nineteen forties. where they show the foibles of human nature and reactions to external pressures. One of the early examples of this genre is Lucky Jim (1954). The image of teacher is swinged in many shapes from the tyrant to the rebellion to the defiant. All is personified in the characters of these

OpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtain

Abstract 

The catalytic cracking conversion of Iraqi vacuum gas oil was studied on large and medium pore size (HY, HX, ZSM-22 and ZSM-11) of zeolite catalysts. These catalysts were prepared locally and used in the present work. The catalytic conversion performed on a continuous fixed-bed laboratory reaction unit. Experiments were performed in the temperature range of 673 to 823K, pressure range of 3 to 15bar, and LHSV range of 0.5-3h^-1. The results show that the catalytic conversion of vacuum gas oil increases with increase in reaction temperature and decreases with increase in LHSV. The catalytic activity for the proposed catalysts arranged in the following order:

HY>H

Ab – initio restricted Hartree - Fock method within the framework of large unit cell (LUC) formalism is used to investigate the electronic structure of Si and Ge nanocrystals. The surface and core properties are investigated. A large unit cell of 8 atoms is used in the present analysis. Cohesive energy, energy gap, conduction and valence band widths are obtained from the electronic structure calculations. The results are compared with available experimental data and theoretical results of other investigators. The calculated lattice constant is found to be slightly larger than the corresponding experimental value because we use only 8 atoms and we compared the results with that of the bulk crystals, nanoclusters are expected to have str

A fast laser texturing technique has been utilized to produce micro/nano surface textures in Silicon by means of UV femtosecond laser. We have prepared good absorber surface for photovoltaic cells. The textured Silicon surface absorbs the incident light greater than the non-textured surface. The results show a photovoltaic current increase about 21.3% for photovoltaic cell with two-dimensional pattern as compared to the same cell without texturing.