Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

Background: Abdominal symptoms are possibly the most frequent of all symptoms encountered in surgical practice.  Pain is the most common of all abdominal symptoms.  Causes of acute abdominal pain include both medical and surgical. Most symptoms arise from intra-abdominal organs or systems while some may originate extra abdominally and are then referred to the abdomen. Medical causes of abdominal pain are encountered more frequently.

Objective: To study the causes of acute abdominal pain in patients attending emergency department in Al- Imamain Al- Kadhimain Medical City.

Type of the study: A prospective cross sectional study

Meth

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Praise be to God, Lord of the worlds, and prayers and peace be upon our master Muhammad and upon his family and companions.
And after:
      The research dealt with an important and critical era in the history of the Seljuk State of the Romans in Asia Minor, as that country, after the assumption of Sultan Ghiath al-Din Kehsaru II in the year 634 AH / 1236 CE, was subjected to the constant Mongol threat, so the research came marked with (the Seljuk State of Rome in Asia Minor and the Mongol invasion 634 - 708 AH / 1236 - 1308 AD) The research showed the succession of the Seljuk Sultans to the rulers whose rule after the death of Sultan Alaeddin Kikbad was weak and subject to the authority of the Mongols

           In the nineteenth century, a new type of cities appeared, known as new cities located on the edges of major cities, and these cities began to  decentralization, urban studies turned to this type of cities to find out the most important reasons for the emergence of new cities and find out what those cities will become . Therefore, we will discuss in this research how the urban emergence of these cities (edge cities) occurs, so the research formulates its problem : The need to know the stages that edge cities go through, ending with their emergence, and the mechanisms that cities take within their context  ( regeneration or adaptation ), Assuming that edge cities are a